Follow the reluctant adventures in the life of a Welsh astrophysicist sent around the world for some reason, wherein I photograph potatoes and destroy galaxies in the name of science. And don't forget about my website,

Tuesday, 18 July 2023

Singing, Summer, Scones, Speeches, Sounds and... Science !

Home is for holidays, but every once in a while it's possible to go for research as well. I don't often go to the UK's National Astronomy Meetings (the last one I attended was in Hertfordshire in 2009 !), but this year it was in Cardiff so I basically had to go. It'd be silly not to.

This time it wasn't practical to take the dogs so it was just me, by plane, but going to Cardiff airport instead of pesky Bristol or London. Even though this involves a 2 hour layover in Amsterdam (an airport which is nice but far, far too large), not having to commute on landing is somehow about ten thousand times more convenient. If only there was a budget airline flying this route ! Oh well, one day.

Getting home before midnight meant I didn't feel absolutely shattered the next day, which was technically the first day of the conference. I began with a nice dog walk followed by a visit to a friends, and then in the evening the welcome reception was in Cardiff Bay.

With an actual male voice choir, which is about as Welsh as Welsh can be.

I learned later that afterwards some people jumped on the conference drinking bandwagon very early, ending up in an axe-throwing bar (those are thing now, apparently) somewhere late that very evening. As it turned out, I think I'm glad I missed that one.

Monday began the conference proper in the shiny new "Centre for Student Life", I guess because calling it the "Student's Union" is too socialist or something. While I quite like the exterior, which is modern but in keeping with the very much older, grander building across the road, I've always wondered why it's so damn big. As it turns out this is very simple : because it's not just a student drinking bar but a whole series of lecture theatres. The largest one, which hosted the biggest sessions, holds 550 people.

The only thing I don't like is the weird layout of the stairs, which don't form a continuous sequence - you have to walk between stairwells on most floors.

The Science Bit

The Conference

Rather than do a day-by-day account of how things went, it's probably better if I just pick out the highlights and other notable points. Overall, this was a frankly ludicrously well-organised conference (and I'm not just trying to sing Cardiff's praises, after all we've got professional choirs to do that). Talks were almost always within 5 minutes of their scheduled time, hardly any problems occurred with the projectors and the like, and there were no major clashes between sessions. 

Where it really stood out, though, was with the catering, which was the best conference catering I've ever had. Coffee and tea were permanently available (unlike in JanFest, where for some godforsaken reason the bastards kept taking everything away during the talks), with a flow system that was second to none, and during the official morning and afternoon sessions were stocked with biscuits, Welsh cakes, slices of Victoria sponge and lemon drizzle cake which were constantly refilled. Lunch was an all-you-can-eat buffet and, surprisingly, the quality of all of this was actually not half bad - I would even dare to say it was outright good, and think some of my more judgemental colleagues must have been a little... spoiled. Given the standard of the local physics department canteen this was an unexpected but welcome change of pace.

If I have a criticism of the conference itself it's that the invited talks probably should have been called "review talks". This sounds minor, and it is. But "invited" suggests to me the speaker is very prestigious and has some exciting new results to present, whereas a review talk is just a summary of everyone else' research : absolutely fine, but a bit weird if you're sat there waiting for something else. 

Solid science

On to the science itself. One thing I was surprised at is that the talks about the epoch of reionisation, when the first stars and other bright sources first lit up and ionised all the gas throughout the entire universe, have changed very little in the intervening 14 years (!)* from when I was last at NAM. But I think perhaps in that respect I've timed this badly : JWST has only just come online, and we may need only another year or two to get some really interesting results here. It looks like those first, stupendously powerful stars are indeed beginning to be found, but we don't have enough information to say anything interesting about them yet.

* Multiple people guessed my age this week, with estimates ranging from 26 to "33, at most". I'm feeling pretty good about that.

On a related front, the recent storm of controversies about whether JWST has found more massive galaxies too soon after the Big Bang appears to be more-or-less over : it hasn't. There was exactly one talk saying we should keep an open mind about whether any of the new results pose fundamental difficulties for the Standard Model but all the rest were pretty clear that this isn't tenable. 

To be fair, it does seem that JWST has found an unexpected number of early disc galaxies, as well as galaxies which have already finished forming stars in the early Universe. But these are rather problems of detail, as several speakers explained at some length on just how many uncertainties still remain in the models - there's more than enough scope in the error bars to solve this without throwing out the basic models at all. 

Problems with the mass, which would have been much more fundamental and interesting, have been resolved with spectroscopic confirmation of the true redshift (effectively, distance). As we all suspected, the photometric redshifts (and I confess I didn't quite realise how sophisticated this technique can be) just aren't good enough, even when multiple fitting models give the same answer. Spectroscopy has definitively but disappointingly shown that the suspected very early, massive galaxies are actually a lot smaller and closer. They're still interesting, but they're not "oh shit I just wet my pants" level of interesting any more. Oh well*.

* As per another talk, however, the "tensions" between the different Hubble constant values obtained by different methods might yet prove to be something more interesting. I hope so, but I'd bet against it.

For the rest, I'll briefly summarise some of my personal favourites :

  • Amélie Saintonge gave a great review talk about star formation in molecular clouds. This interests me in how it relates to star formation on larger scales : can we relate global conditions to local activity ? It seems that we can at least in part. Self gravity seems to be important only in high-pressure environments, and only the densest part of each cloud actually forms stars - there may not be a simple global threshold at which star formation happens. 
  • Timothy Davis also looked at molecular gas but this time in galaxies experiencing gas loss. Oddly, galaxies in the Fornax cluster have less molecular gas than expected, while those in the more massive, more gas-lossy Virgo cluster have more normal molecular contents ! There seems to be a consensus rapidly emerging that as the thinner atomic gas is lost, initially part of it can be compressed and form molecules. So during the active stripping phase, galaxies have a bit less atomic gas than normal, but can even have more molecular gas than they usually do.
  • An honourable mention to Elizabeth Watkins for making a catalogue of gas bubbles and doing it correctly : by eye, without any boring algorithms. I'm a big fan of this approach and I think it would do everyone the world of good to acknowledge that we can't be purely objective all the time.
  • Ben Thompson showed that ram pressure stripping, which we normally associate with galaxies moving at the highest speeds in the densest parts of galaxy clusters, can also happen the the edges of galaxies voids. Here the densities and speeds are very much lower so this is not what one would naively expect. It seems that while ram pressure here is never going to be as damaging as it is in clusters, it might still be enough to strip the outer reservoirs of gas, slowly quenching star formation rather than bringing it to a sudden halt.
  • Ethan Taylor (no relation) gave a cool talk on the overlap between dwarf galaxies and globular clusters. This series of simulations is to try and find tests to probe the nature of dark matter : globular clusters and dwarf galaxies can have similar stellar masses, but the former don't have any dark matter whereas the latter have lots. His simulations look for objects in between the two. I asked if this could relate to Ultra Diffuse Galaxies (which are awash with such controversies) but alas it seems not, as those are much more extended objects.
  • A dis(?)honourable mention to Mac McMullon who had all the best quotes, including, "Dwarf galaxies, woooo !", "I had more fun fonts but Micosoft ate them", and of course, "I've got a badass hangover." Back atcha, Mac, but just wait until you give your presentation in the afternoon and can still complain about your hangover - then we'll talk.
  • Finally, David O'Ryan for introducing a code I want to try which seems to be a very sophisticated way of finding the initial conditions of interacting galaxies. It's not yet public but I can imagine this being a godsend for understanding crazy systems like Leo.
  • Oh, wait... me ! I gave a crazy-fast distillation of 17 years of research in 10 minutes, summarising the major candidate dark galaxies we've found and how plausible they are. Everyone laughed at the right points, so I guess I wasn't going too much at breakneck speed. Though, while I do like to play the hahah-all-you-chumps-are-interested-in-star-formation angle (whereas I'm looking at gas clouds that don't do anything), I do think there's a serious point people are overlooking here : what keeps some objects dark while others which are apparently otherwise very similar are optically bright ?


There was also some great stuff here about not science itself but the process of how we do science : diversity, outreach, and the overlap between science and the arts. There was also a modicum of some truly awful stuff. Now I'm probably going to annoy absolutely everyone when I say the conference was very, very woke, because I mean this in two senses : it had an aspect which is unconditionally, unequivocally and unarguably a Good Thing (everyone of any race, creed, cast, colour, faith or sexual orientation should be able to become a scientist; if you don't believe this, you need to rethink your life choices), but also in the more colloquial pejorative sense. That is, a sort of militant, beatings-will-continue-until-morale-improves approach, you WILL pro-actively embrace all forms of diversity and tolerance or else you'll be taken outside and shot. 

Two particular comments stand out regarding the latter. First, a throwaway comment on one of the talks about how science is "colonialising", which I think is utter rubbish. Academia ? Maybe. But science itself ? Simply nope, this is a hideously weird thing to say. Secondly, a suggestion that if countries which unfairly discriminate against LBGTQ/etc., we should boycott those countries. The problem here is that I vehemently despise the current UK "government"'s policies and rhetoric regarding refugees, asylum seekers and the poor. Should I therefore have boycotted NAM ? I don't think so. If I did that, I'd probably have to boycott every country.

I retain the anonymity also of one additional speaker who presented a piece of outreach which has been very successful but, on seeing it, I have to say I personally hated it. I don't hate the goal of inclusivity, obviously. No, I hate the "let's ram this down everyone's throat* and forget to tell them any actual science" approach. Yes, damnit, include as many characters of different ethnicities, ages and backgrounds as you want : the more the merrier. But treat those characters with genuine respect. Show them enjoying research, yes, but show them having difficulties too, just like everyone else. "Happy People Doing Science", encountering no kind of difficulties whatsoever - not so much as an angry bee - is something that is monumentally boring and unbelievably cringe-worthy.

* In other words, "We need MOOAR EXPOSITION about racism ! MOOOOAR !". Come on, this is not an information deficit problem any more. I thought a much better approach was described in another talk : educating teachers and students together, en masse and repeatedly : that's how you beat implicit bias, not by constantly telling everyone "racism is bad" because everyone already knows this. As in Damon Centola's Change, implicit bias happens because of culture, not conscious choices where anyone sits down and thinks, "hmm, how can I fuck the libtards today ?". The only way to tackle this is to change entire groups, not by educating individuals.

A much better message was in a talk of Peter Coles. He gave two outstanding quotes. First, "If you're upset about pronouns, wait till you find out about adjectives", and secondly, "do the best you can to make your work environment the best it can be for people who are not like you." So far as lifestyle choices go, I thoroughly agree (I found it interesting from another speaker that in other countries it's common to end a science talk with a Bible quote, which might not go down well elsewhere !), though I might have some qualms about Flat Earthers. As usual, the question, "where do you draw the line ?" is a legitimate one which can and should actually be answered, and is not merely rhetorical.  

But I'm not in a mood for an extended rant about this, so I'll move on to what was for me the stand-out talk of the whole conference : a presentation about Gavin Starks and Andy Newsam's soniverse. This gloriously insane idea began with the simple enough process of sonifying data cubes, turning radio spectra into audio. This seems to work better than I would expect it to; I'd love to incorporate this into FRELLED somehow... but they've gone much further. They're developing a theory of the universe (just purely for shits and giggles I think) in which photons are replaced with sound, so that dark matter becomes silent matter, a batshit crazy resurrection of the aether.

Utterly bonkers. I absolutely love it.

The Social Bit

The non-conferency bits attached to the conference were numerous. We began with an opening address by First Minister Mark Drakeford. Remarkably... he was genuinely funny. Now I quite like the guy but I do normally think of him as the world's most boring hamster. No more. The previous speaker was the vice chancellor, who expressed some skepticism about claims of Roman astronomy in Wales. Drakeford said he wouldn't normally presume to correct him, but went on to list numerous examples, which he described in some detail, of pre-Roman astronomical alignments in ancient Welsh megaliths. It was a well-researched, highly sympathetic speech that in terms of the old golden rule "know your audience" had it utterly nailed. And he was indeed funny, noting, "from the financial crisis to the austerity crisis, the Brexit crisis to the COVID crisis and the cost of living crisis, we move, seamlessly, from one damn thing to another"; and "politics is more akin to astrology than astronomy." Which was delivered with impeccable comic timing that perfectly matched his delivery. It was hardly stand-up, but it bordered on Yes Minister territory.

The line on the whiteboard is from one of the few presentations where things went awry and the speaker was forced to draw a missing graph.

Monday evening featured the usual NAM 5-a-side, but I was infinitely more impressed by Mike Edmund's one man Tuesday play, "Sir Isaac Remembers". Mike is now President of the Royal Astronomical Society no less, but a long time back he was my undergraduate academic tutor. Had the X-rays been available on time, my Masters project would have been studying the Antikythera mechanism rather than running galaxy simulations. Oh, the road not taken... Anyway, the play is Mike in character as Sir Isaac narrating a random assortment of his letters and writings, which is both hilarious and educational (genuine edutainment !). It has to be experienced, not described, so I won't try.

After this we had a quiz. We came third, which is not bad at all considering there was certainly well over 100 people participating. Actually this was reportedly the largest NAM ever, with ~650 attendees, although no-one is quite sure why.

Wednesday was the conference dinner at the Millennium Stadium*. Excellent food, plentiful wine, and for £40 it wasn't cheap but I would honestly say it was good value. The one downside was the endless bloody awards, which meant that it was hard to have a conversation with anyone because if nothing else everyone had to stop every two minutes to give a round of applause to someone they'd never heard of winning an award they'd never heard of for research they weren't interested in. However, then we all went out and got very, very drunk, so that was alright in the end.

* Why no, I won't call it the Principality Stadium, you twerps.

Thursday evening had nothing much scheduled, but a surprising number of people went out again and everyone was complaining the next day except me because I went home and had a lovely night's sleep. Mwhahah, bitches.

The Holiday Bit

This was wise, because the conference ended midway through Friday afternoon, whereupon I proceeded down to the bay for the annual Food Festival, and afterwards proceeded to get very drunk again.

The rest of the week was divided between walking the dog...

I am horrified to discover that the local dogging spot appears to have been taken over by some sort of death cult. Also, while it was mostly dry, there were times when it rained a lot. Which it's supposed to, because it's Wales.

... buying and reading books and enjoying other local delicacies (the first set are not mine, I just think the juxtaposition in the bookshop is... interesting) :

I always want to put the jam and cream the other way around on one scone just to annoy the internet. But come on, the jam is sticky so it goes on the bottom. Trying to spread jam on top of the cream is just asking for trouble.

... continuing to drink until silly o'clock and also exploring Penarth :

This toilet foyer in an an otherwise perfectly nice seaside restaurant/bar is the single chaviest thing I've seen in my life. There are more horses' heads elsewhere, positioned so that they look like they're following you around the room.

And then finally it was time to come home.

About the flights there isn't much to say. Everything went as smoothly as possible, we even took off and arrived either slightly early or dead on time for all flights. I should also mention that Cardiff airport is only marginally larger than I remember it (I went through it back in 2008 for a flight to NAM which that year was in Belfast). It was practically deserted, with only four flights on the whole board, but it could probably comfortably accommodate and feed ten times as many people as were actually present.

Anyway, it was a lovely couple of weeks. As well as catching up with all the most important people, I also ran into people I haven't seen in a good ten years. Whether that's enough to persuade me to go to next year's NAM in Hull, however, is another matter.

Sunday, 18 June 2023

Flying Backwards Through Time

I've tried to make this video as self-explanatory as possible, so here it is without further ado :

This will be a short post just to give a bit more detail and some static images.

I was feeling really inspired and motivated by the recent solarigraphy meeting. I haven't made any dedicated data visualisation projects in a while, but one that's been gestating in the back of my mind is to try and show the dark matter in galaxy simulations... I think showing this as trails (a la the Sun in solarigraphic images) might look interesting.

But first, there's much lower-hanging fruit to pluck, though in a tangentially similar vein. Back in 2018, I decided it might be fun to try a time lapse from the office. Specifically, here, looking down the Jihozápadní V avenue.

Red X marks the spot.

So each time I went to the office, for the next ~16 months, I took a photo on my mobile phone, which was then a Huawei P10 lite. I tried to keep things as stable as I could, trying to get myself in the same position each time and lining things up in a similar way, but this was all done very quickly and by hand. I decided to do this particular view basically on a whim : it's somewhere I was present regularly and reliably at about the same time, it's quite a nice view, and looking in the other direction (towards the institute itself) you don't see so much. From the other direction, where you enter the avenue to go towards the institute, at certain times of year one gets a very nice "Stonehenge" effect :

Looking in the other direction avoids the sun being in the frame and I'm not sure if this was the right decision or not. I do wish I'd gone for landscape format, but having to avoid the tops of the trees would probably have annoyed me quite intensely.

Anyway, I didn't always manage to take a photograph every day. Sometimes I just forgot, occasionally going back later when I remembered (or if there were inconveniently-placed people that I hoped would bugger off if I left it for a bit). Sometimes I was away for conferences or holidays* (maybe even working from home from time to time !), and of course I wasn't there on weekends at all. Also the time of day varied considerably, from 7:45 am (God knows what that was all about) to 5:36 pm (probably I forgot to take the picture in the morning). The median time was 9:47 am, with a standard deviation of 1 hour. 

* Worst of all for this project, I tend to take holidays in the spring an autumn, so the most crucial moments of seasonal change are missing !

This is about as good as can be expected from a real-world side-project, where it's just not possible to keep things more controlled. So not only does the camera position vary quite a bit, but so does the lighting - and of course, this varies dramatically depending on the weather.

The result is the first sequence in the video - not much more than an unpleasant mess. We need not dwell on it any longer.

I was expecting as much. I knew I'd probably have to manually align the images to get a nice result, but somehow I just never got around to doing it... until now. So I imported all the images in Blender as transparent planes and manually aligned them by adjusting their scaling, rotation and location. If we show all the images together, here's the unaligned result :

Which explains why the animated sequence is such a mess. Here's the version after doing all the corrections :

Little bit of contrast adjustment on this one.

Much better. Probably there are better ways to do this; certainly there are a few cases where I didn't align things as well as I could, probably it could even be automated. But I enjoyed the process, so never mind. I'm also pleased with the way the colour turned out, and the blur gives it an air of authenticity, like it's from an archaic film camera instead of a modern electronic gizmo. Still, while the resulting animation sequence is far more bearable than the raw version, it's not quite as good as I was hoping for.

But together with all the long-exposure stuff I'd seen in the solarigraphy meeting, this gave me ideas of how to process the images differently. Why stop with a simple, traditional sequence of images ? These combined images are in effect pseudo-long-exposure photographs, compressing 16 months into single stills. They're not the same as proper solarigraphs of course, but the overall effect is similar in that you see multiple times all at once.

So I tried combining the images in different ways for the animation. The simplest approach, which gives a result I quite like, is to give all the images the same level of transparency, such that only when they're all combined do they become completely opaque. That's what's shown in still images above. In the animation, it gives very a much smoother animation than the original, and you still get a satisfying sense of change as it progresses. 

But why insist we see all the images ? If we restrict it so that only 30 images (one month) are ever shown on screen, and their transparency is such that their sum is fully opaque, then we get the best of both worlds : a nice smooth transition but with a more pronounced sense of change.

Choosing four images to give an obligatory "four season" compilation. We had a particularly hot and dry summer that year, with all the grass dead and even the trees looking unhealthy. Fortunately we also had a cold, snowy winter.

Finally, using the same technique I do for astronomy data visualisations, we can also show the data as a pseudo-3D volume. In effect this has been done already : the images are all separated along the into-the-screen axis, it's just you can't see this because the rendering disables perspective. If we enable it, we get this funky volumetric effect. I really like this in the animation, you get a sense of movement that's only partially true... the camera moves back from the images, but that's not the same as really moving through the street. It's actually moving backwards through time, a weird quasi-movement away from the images but not through the street itself, all the while showing images from longer and longer ago.

Or equivalently, in this image you're looking into the future by looking at the centre, and into the past by looking at the edges. Time is treated as a spatial dimension.

This concludes my brief foray into experimental photography. You may go about your business, and I'll get back to the world of astronomy.

Friday, 16 June 2023

Working On Sunshine

Staring At The Sun With Solarigraphy

Image by Diego López Calvín. Always reminds me of the time travel sequence in The Time Machine.

Alas, I can't take credit for the post title. It's something I once heard someone joke should be the official anthem of solar astronomers, though I've long since forgotten who it was. Anyway, last week I was lucky enough to attend a conference on solarigraphy, and I think this is worth a post.

Now as an extragalactic astronomer the Sun is our great foe in the sky that does naught but blind us all and make us wince in pain and fear. And to be honest, professionally my interest in the Sun is practically zero. Furthermore I'm somewhat averse to stepping so far outside my astronomical lane that I end up in a subject which is really another topic all together; some people even call solar science a branch of geophysics.

But this meeting was arranged as a combination of science, art and education. And there things get much more interesting to me, which is how I came to be on the local organising committee.

Solarigraphy is an unusual photographic technique which is at once incredibly simple and incredibly subtle. On the first day we had a little workshop where we made our own cameras. It consists of cutting open a can (in this case a beer can from our sponsor), making a pinhole*, adding in some photographic paper on the opposite side, and then  and this is the only tricky bit  quickly taping it in place before it gets a significant level of light exposure, and finally sealing the can back up with more tape.

* With a pin.

The small piece of tape on the lower part of the can (right image) is a shutter, to stop the camera from exposing before it's ready.

This incredibly simple device can produce remarkable images. You have to leave them for an extended period  typically six months but the results can be fascinating.

The basic idea is to capture the paths the Sun makes through the sky, which varies throughout the year. With just a pinhole and a sheet of paper, you can capture both the solar tracks but also the landscape. The phenomenally long exposures (one claimant for the record is eight years) means you get something which is essentially the reverse of the T-Rex's vision in Jurassic Park : solarigraphy can only see things which don't move. Unless something appears consistently in the same place, you won't usually see it in the final image.

On the other hand, a predator from which you can run but never rest could be pretty damn threatening too. 

There are a lot of nuances to the technique and I'll describe a few of them in the course of recapping the meeting. The cameras themselves, though, really do tend to be extremely simple. The difficulties of using them are pragmatic : you have to find somewhere to place them where they won't be disturbed for a long time, you have to orient them so the rainwater can drain out, you have to fix them securely so they don't move about on their own. You don't need to develop the paper though : it does that all by itself. Instead you just digitally scan and process the sheet when you're ready. 

Depending on what goes right and what goes wrong, you can get an incredible diversity in the final results. Some look like professional-grade photographs whereas some look like Jackson Pollock caught the norovirus from a vomiting unicorn. As someone said, if you place two identical cameras in the same location for the same time, you'll still get two completely different results.

Without further ado, here's my summary of the meeting and the bits I found most interesting.

The Meeting

Day One

The 2nd International Solarigraphy Meeting took place in Ondřejov, a small village about 40 km from Prague. The only feature of note here is that it's home to Ondřejov Observatory, the much larger half and headquarters of the Astronomical Institute which employs me, and it's where the main meeting organisers are based.

We began with a talk by head honcho Maciek Zapior who introduced the topic (you can see some of his own solarigraphs on his web page). This was great for muggins here, as probably the only participant who'd never attempted any solarigraphy. Maciek covered not just the technique but also the wider context of the intersection of art and science : there's a search for beauty and truth, arguably, in both. Now personally I think the Universe is a great big bloody mess, but that the topic was raised was far more important than agreement, with these kinds of discussions for me being generally limited to online stuff. Incidentally, the name comes from the 1961 novel Solaris.

Next we had a talk by Cezary Bartczak about camera construction, especially pinhole cameras in general, which can range from the simple can constructions* to heavy-duty 3D printed versions. They're really quite satisfying objects in their own right, and now I wish I'd tried the "make your own pinhole camera" sets when I was younger. Note that pinhole photography in general does rely on chemically developing the image, whereas solarigraphy does not.

* Why IN GOD'S NAME don't we have a website called Only Cans ???

Following this we had the "build-a-solarigraph" session for which you've already seen my efforts above. It's going to be tough to find somewhere I can put this, but I'll have to try. Then there was an exhibition of a solarigraph contest which featured some very impressive images, which starts to introduce how flexible this technique can be :

See the link above for details. Some of these images were taken on a bicycle (!) and with a rotating turntable to produce intersecting solar trails rather than the usual continuous set.

This one is from Krzysztof Winciorek which shows a building in construction. I love this weird partial transparency, showing multiple times all at once.

I believe this one, by Łukasz Ciesielski, is of a car hubcap.

In the afternoon we had the online session. Apart from the first speaker, who didn't want to be recorded, you can watch the whole thing below, or just continue reading for my summary of the highlights. As a session all from non-scientists, I found this to have some of the most interesting talks of all. 

We began with Tarja Trygg, who initiated a Global Solarigraphy Project to image solar trails at different latitudes : at the equator the Sun goes vertically overhead, while at the poles it's almost horizontal. She noted that colours appear even on black and white paper, on which more later, and that solarigraphy makes the invisible visible (like imaging wavelengths we can't see directly, but in a very different way). Weirdly, when she started the project she asked people if the photographic technique was viable and was greeted with extreme skepticism. Why this should be, I don't know.

Next was Pablo Giori, one of the directors of the Experimental Photo Festival. This was very art-heavy and not all of it was to my taste... I can't say I'm ever going to "get" Dadaism; to me this looks like the cartoons in Monty Python. More interesting was his history of photography as a process of revolution, homogenisation, and democratisation. I normally find the latter word is heavily overused but in this case it's absolutely appropriate : photography today is available to everyone. Pablo noted that experimental photography is in the mindset, not the technique, with most photos today being "visual rubbish" of no artistic value. 

In this I think he's right but missing the point : most photos today are taken for communication and shared experience, not for artistic value at all. I take pictures when I visit famous landmarks not because I expect to do better than the thousands of professional photos that already exist, but because (a) there's no point in not taking them given how easy it is, (b) to have something that is mine, to remember what I saw. Pablo's talk was also very anti-capitalist, and though I tend to sympathise, I think he might be rather heavily overstating the case. I'm just not convinced that there's any sort of malevolence at work when it comes to Big Photo.

After a break we resumed with photographer and lecturer Justin Quinnel. I think this was probably the most fun presentation of all of them, full of engaging anecdotes of successes and failures. While I strongly agree with the need for outreach and education, I disagree that this shouldn't be digital : digital exploration is absolutely as valid as any other medium.

Possibly my favourite talk was by Michael Wesely for the clear presentation and sheer quality of the images, which are technically amazing. I liked very much his description of standard short exposures as presenting an illusion of stability : the reality is that all things are in constant (though varying degrees) of motion, and in some ways the long exposure photographs actually present a more correct view of the world  they aren't just a blur, they encode all the time information, events and stories as well as brief moments. I really liked some of the images where the buildings were in the process of construction, giving a powerful effect of seeing through time.

It's also worth noting that these are inherently privacy friendly because unless you're dead*, you won't show up well at all in a solarigraph. Wesely took an eight hour exposure of himself (which I think must have been agony), but only with strenuous effort did he appear as anything more than a blur. The vast majority of people show up only as interesting trails. The next talk, by Corine Dufresne-Deslières, picked up on this theme, also noting how if data is unlocatable, it's also unaccountable.

* If we really want to get noticed, we could try doing (a) solarigraphic porn or (b) going full Channel 4 and doing a solarigraph of a decaying corpse.

The final talk of the session was by artist and teacher Heather Palecek, who initially had no realisation that solarigraphy was an astronomical technique but approached it from the perspective of nature. In contrary to the more typical approach of striving for technical perfection, she likes the effects of nature interfering with the images : dirt, mould and water can all influence the colours that develop on the paper, sometimes leading to very surreal but striking images. This all made me wonder if there are any animals that experience time in this greatly sped-up way  I know some experience the world at a much faster pace than we do (hence their incredible reaction times), but I wonder if maybe snails have solarigraph-like vision...

Day Two

Maciej kicked off with a review of the current state of the art. He showed some more novel uses of the images, such as exposures of a single day where you get just one, dramatic-looking solar trail. Others used manual recolouring to give a more realistic appearance, which divided audience opinion. Some thought this meant it was "just a graphic" (whatever that means) while others thought it was clearly the better image. I lean towards the latter, as long as the process is clearly explained. While I do think that any art should have some immediate, self-explanatory value (hence that stupid, moronic painting of a can of soup is just the work of an ultra-pretentious tit, in my view), knowing the process behind it can at least add value.

He also mentioned, especially their NxN project. This hammers home the importance of post-processing, with different artists coming up with very different versions of the same raw image. It's even possible to do solarigraph time lapses, although who claims the title of the "first" is open to debate (Maciej is not a fan of the superlative contests, and I tend to agree - that eight-year exposure image looks quite nice but is nothing extraordinary compared to some much shorter images). Finally he mentioned that you can buy pre-made solarigraph cameras for €20 online, which is just insane considering the total manufacturing cost is probably more like €2 and it takes ~5 minutes.

The afternoon social events included the obligatory visit to the telescopes, another solarigraphy exhibition, but also something much more unusual : a saxophone performance inside the dome of the 2m telescope. In the dark, with the saxophonist accompanied by Maciej who walked around with a torch looking for pieces of sheet music. Well, that's something I've certainly never experienced before.

The cars are very interesting. Here there were different cars parking at approximately the same spot each day, resulting in what Maciej calls a "generalised" car. In other images you can see sun reflections from moving cars in the parking areas.

In the evening we went to a nearby village for dinner, where I was sat with a wickedly mischievous older Polish gentleman. He spoke, very, very slowly and deliberately, and proceeded to tell me how he personally had helped convince Sean Connery to become a Scottish nationalist. For this reason, when the next day in the discussion session he declared that, "there's no emotion in art, that's all rubbish", and that solarigraphy is evidence that the Sun goes around the Earth... he probably wasn't being entirely serious.

On returning to Ondřejov I found it was a very nice evening so I went to the field of radio telescopes to watch the sunset.

In keeping with the experimental photography vibe, here's the Sun through a radio telescope.

Day Three

The morning session was pretty intense. We kicked off Łukasz Rogiński and Jakub Pacuk, who shared their first year of experience in solarigraphy  some of these images were really impressive, and I wish I could find them online. Grzegorz Hussak then showed us a solarigraph taken using a glass negative instead of the usual photographic paper, and while the contrast is extremely low  barely visible  on the physical glass itself, the digital scan was certainly clear enough. 

Maciej took over the next slot due to our only cancellation, resuming the discussion of the current state of solarigraphy. Again, many more amazing images  the single solar track during the eclipse was particularly nice – and more anecdotes of how people respond when they find the cameras in the wild. Some think they're part of geocaching and leave stuff inside. A few people, weirdly, take them away only to return them again. Some leave notes apologising. He moved on to solarigraphy as both an art and science, wherein art is free to treat time as a substance while in astronomy it can be thought of as an angle. He concluded with using automated shutters to trace analemmas and create more arbitrary patterns in the sky.

Next, Alexandre Sampaio  a professional theatre director and photographer  gave us a description of a solarigraphic tour of some Spanish islands he's doing... well, it's nice work if you can get it. Some of his images were great, especially one with a fountain where you could see both the water and solar trails at once. He also gave us a delightful naming contest for alternatives to solarigraphy* : the winner was "let-it-go-let-it-go-graphy", but I much preferred, "it's-a-blur-but-I-call-it-art-agraphy". Oh well, can't win 'em all.

* I can pronounce solarigraphy just fine in my head, but I always stumble on it physically. I find solargraphy very much easier.

Finally, chemistry researcher Tomáš Slanina gave us a really interesting, totally different talk on the chemistry that makes solarigraphy work, and photoreactivty more generally. He gave a few amazing demos where he mixed different chemicals in beakers and you could see them shining in UV light. For photographic paper, light causes silver nitrate to solidify, which makes it opaque. Why the different colours appear I'm not sure, but this appears to be the result of something more complex.

After a break, professional artist Helena Jiráková began the final session with a talk on art in astronomy. She covered the works of many artists besides herself, including Nancy Holt's Sun TunnelsJames Turrell's Skyspaces and Roden Crater, Chris McCaw's use of the Sun to literally burn tracks in film, and perhaps my favourite, Olafur Eliasson's spectacular artificial indoor sun made of hundreds of lamps with a mist of sugar water.

Then it was my turn; I've put my slides online here. There was very little new content here but I assembled it in a different way for a different audience. I began with a very brief overview of galaxies and described how radio data tells us about the invisible dark matter, using that old exploding galaxy sim to start things off. I described how radio receivers work and the importance of understanding that they're spectrographs, so they collect frequency data as well as brightness. Receiving 4,096 frequency channels all at once somewhat compensates for having only seven spatial pixels to work with... and it also means you have a lot of freedom to choose how you render the data.

I began with the standard approach of channel maps, in which each frequency channel creates a different image, moving on to volumetric rendering by way of the glass cube and a 3D movie. Then I tried to address Maciej's comments about truth by showing the exact same data set rendered in four different ways : channel maps, height maps, volumetrically, and isosurfaces. You really do get different information from the data if you just look at it differently.

Pablo Giori had said that art isn't in the business of truth; Michael Wesley that it was all about stories, and various others that it's all about different perspectives, self-discovery, empowerment etc*. My take is similar. How you visualise your data really does affect how you interpret it, not just aesthetically but also scientifically : some information is far easier to discern using one technique than another. I think none has a claim to be more valid or true than another, but each can be more appropriate for tackling different questions. I ended with an overview of my efforts to turn HI data into art, which I don't need to recount here because you can just see that link instead.

* It was a very, very woke meeting.

It's always fun to see audiences looking silly.

People seemed very enthusiastic about all this and I came away with an adrenaline buzz that always accompanies a successful talk. In fact, it's inspired me to pick up a project that's been on hold for four years  with luck, that should be the next post here in a couple of weeks or thereabouts, so watch this space.

The final talk was Zbigniew Makarewicz on science as art and politics. This was interesting, though at times hard to follow (what he meant by saying that art was aristocratic I'm not sure). He began quite delightfully with something along the lines of, "Thank you all for indulging my sadistic tendencies, especially Mr. Taylor for speaking English". He proceeded to say that painting is not art, that an artist is someone who creates something of special quality. Art, science, technology and politics, he said, are all interconnected in common culture : they are separate endeavours but do not exist in isolation. And again, he noted that artists and scientists view the same data in different ways, resulting in different works. Einstein viewed the world as equations, Bohr as something more poetical. 

It was all very heady stuff. I liked it a lot, even though so many speakers had the unfathomably bizarre tendency of having laptops with desktops in which every available space was occupied with an icon. It's all well and good to meet new people and get different perspectives, but there are limits. So for now, it's back to science I go.

Friday, 26 May 2023

All Hail Our Benevolent Robot Overlords

Visions of possible technology-based futures generated with Bing Image Creator.

Certain topics demand that any self-respecting blogger offer commentary on them regardless of their expertise in the area. The recent explosion of AI tools is one such field, so here, for whatever it may be worth, is my take on the matter.

For a long time, I've had three rules to keep in mind when assessing any claim of a significant advancement in artificial intelligence :

  1. AI does not yet have the the same kind of understanding as human intelligence.
  2. There is no guarantee rule 1 will always hold true.
  3. It is not necessary to violate rule 1 for AI to have a massive impact, positive or otherwise, intentional or otherwise.

These I devised in response to a great deal of hype. In particular, people tend to be somewhat desperate to believe that a truly conscious, pseudo-human artificial intelligence is just around the corner, and/or that the latest development will lead to immediate and enormous social changes. I could go on at length about whether a truly conscious AI is likely imminent or not but I think I've covered this enough already. Let me give just a few select links :

  • Some examples of how badly chatbots can fail in laughably absurd ways, and a discussion on what we mean by "understanding" of knowledge and why this is an extremely difficult problem. 
  • A discussion on whether chatbots could be at least considered to have a sort of intelligence, even without understanding or consciousness or even sentience (another, closely related post here).
  • Finally, a philosophical look at why true consciousness cannot be programmed, and that even if you reject all the mystical aspects behind it, it's still going to require new hardware and not just algorithms.  

Given all this - and much more besides - while I do hold it useful to remember rule 2, I doubt very much that there's any chance of a truly conscious AI existing in the foreseeable future. So instead, today I want to concentrate on rule 3, what the impact of the newly-developed chatbots might be in the coming months and years despite their lack of genuine "intelligence". 

Because this seems to be such a common misunderstanding, let me state rule 3 again more emphatically : just because a robot doesn't understand something doesn't mean it isn't important. Nobody said, "huh, the typewriter can't think for itself, so it's useless", and nor should we do so with regard to language models and the like. Throughout all the rest that follows I will never assume that the AI has any true understanding or awareness - as we'll see, it isn't even reasoning. The prospect of a truly thinking, comprehending AI is a fascinating one, but getting utterly fixated on the notion that "it's not really AI" is simply foolish. There's so much more to it than that. 

A Family of Futures

As I see it, there are a few broad ways in which AI development (or indeed anything else) could impact society. A visual framework of a selection of these will help :

Note the y-axis is not at all the same as the performance level of AI.

I'm assuming they're all monotonic just for simplification; in reality, all such curves would be a lot more wiggly but that's not important for my purposes. The different paths can summarised :

  1. Utopian singularity. AI will soon render all jobs obsolete and enhance productivity to such stupendous heights that its exact impact on society is unforeseeable, but clearly all to the good - or so much so that the positives far outweigh any negatives. Whatever it is humans end up doing, in this trajectory, it will be massively better than what it is now.
  2. Exponential improvement. Here AI causes continuous, massive improvement, but never reaches a true singularity. At any stage the effects are predictable, though of ever-increasing magnitude and speed. Social improvements are vast, but never amount to a fundamental change in the nature of human existence.
  3. Linear growth. Of course this could be of different gradients, but the behaviour is the same : a steady, predictable, continuous change without upper limit, but always manageable, rarely disruptive, and never revolutionary.
  4. Asymptotic growth. Resembles linear growth at first but eventually reaches a plateau beyond which no further improvements are seen. In essence, this would mean there is a fixed maximum potential this technology can achieve, and though this has yet to be reached, progress beyond this will require wholly new developments.
  5. No real change at all. Claims that the current technology is not likely to cause any substantial further changes beyond what's already happened.
  6. Asymptotic decline. Like 4, but AI makes everything worse to some fixed point. E.g., it has some limited capability for misinformation or cheating in exams, but which cannot be exceeded without new methodologies. 
  7. Linear decline. This is quantitatively similar to path 3 but the effects are qualitatively different. Continuous, predictable improvement is manageable. Continuous, predictable degradation is not, e.g. knowing you're running out of resources but continuing to consume them anyway. This is erosion rather than collapse, but it still ends indefinitely badly.
  8. Exponential fall. Perhaps there's no limit to how awful AI or its corporate overlords can make everyday life for the overall population, such that eventually everything falls into utter ruin. At least it's quick compared to path 7.
  9. Apocalyptic dystopian singularity. Like The Matrix and Terminator except that the machines just win. The robot uprising which eventually results in the total extinction of every biological organism on Earth.

This is quite the range of options ! And different sources seem to favour all of them with no consensus anywhere. Before we get to what it is AI can actually do, I think it's worth considering the social reasons people hold the opinions they profess. So let's take a look at the which of these are most commonly reported and by whom.

Who says what ?

The most commonly reported paths seem to be 1-2 judging by the AI subreddits, 5 judging by my primary social media feed, and 9 according to mainstream media. Ironically, the extreme options 1 and 9 are fuelled by the same sources, with the developers so keen to emphasise the revolutionary potential that they're apt to give warnings about how damn dangerous it is. A clever marketing technique indeed, one that strongly appeals to the "forbidden fruit" syndrome : oh, you want our clever tech, do you ? Sorry, it's too dangerous for the likes of little old you ! Please, I'm so dangerous, regulate meeeee !! And most egregiously of all, Please stop AI development so I can develop my own AI company to save us from the other ones !

Open AI seem to be playing this for all it's worth. They insisted GPT3 was too dangerous to release, then released it. And take a look at their short recent post supposedly warning of the dangers of superintelligence. It's marketing brilliance, to be sure : don't regulate us now because we're developing this thing which is going to be absolutely amazing, but with great power comes great responsibility, so definitely regulate us in the future to stop it getting dangerous. It's an audacious way of saying look how important we are, but in my view there's little in the way of any substance to their hyperbolic claims.

Path 5, by contrast, seems to be entirely limited to my honestly quite absurdly-jaded social media feed (with some preference for 6 in there as well). It's not just one or two individuals, but most. "It's just not useful", they say, even as ChatGPT breaks - no, smashes - records for the fastest gain in users. This is wholly unlike my real-world colleagues, who I think are generally more inclined towards 3 or 4.

I suspect the social media crowd are conflating the AI companies with the technology itself. And yes, the companies are awful, and yes, how its used and deployed does matter - a lot. But just because someone wants to sell you a subscription-package to use a printing press would not mean that the printing press itself was a useless trinket with no real-world applications. It only means that that person was someone in need of a good slap.

Claim 1 : This will not be a non-event

This prospect of no further change seems the least defensible of all the possible trajectories. I mean... sure, tech developments are routinely over-hyped. That's true enough. But spend more than about five seconds comparing the technology we use routinely today with what we used a century ago... ! Even the internet and mobile phones are relatively recent inventions, or at least only went mainstream recently. A great deal of technological advancements have come to fruition, and have transformed our lives in a multitude of ways. Technological progress is normal.

What's going on with this ? Why are some very smart people using the most modern of communication channels to insist that this is all just a gimmick ?

Several reasons. For one thing, some developments are indeed just passing fads that don't go anywhere. 3D televisions are a harmless enough example, whereas cryptocurrencies are nothing short of an actual scam, blockchain is all but nonsense, and "NFT" really should stand for "no fucking thankyou" because they're more ridiculous than Gwyneth Paltrow's candles. You know the ones I mean.

That's fair enough. Likewise all developments are routinely oversold, so it makes good sense to treat all such claims as no better than advertising. Another reason may be that AI has been improperly hyped because of the whole consciousness angle; proceed with the expectation that the AI has a genuine, human-like understanding of what its doing and it's easy to get disillusioned when you realise it's doing nothing of the sort, that passing the Turing Test just isn't sufficient for this. It was a good idea at the time, but now we know better.

And I think there are a couple of other, more fundamental reasons why people are skeptical. Like the development of VR and the metaverse*, sometimes are impacts are strongly nonlinear, and aren't felt at all until certain thresholds are breached. This makes them extremely unpredictable. Development may actually be slow and steady, and only feels sudden and rapid because a critical milestone was reached.

* See link. I've seen a few comparisons between VR and AI, claiming they're both already failures, and they're born of the same cynical misunderstandings.

For instance, take a look at some of the earlier examples of failing chatbots (in the link in the first bullet point above). The fact that AI could generate coherent nonsense should have been an strong indication that immense progress was made. Simplifying, the expected development pathway might be something like :

Incoherent drivel -> coherent nonsense -> coherent accuracy.

But it's easy to get hung up on the "nonsense" bit, to believe that because the threshold for "coherency" had been breached, that didn't imply anything had been achieved on the "accuracy" front and wouldn't be so anytime soon. Likewise, even now we're in the latter stages, it's easy to pick up on every mistake that AI makes (and it still makes plenty !) and ignore all the successes.

Finally, I think there's a bias towards believing everything is always normal and will continue to be so. Part of the problem is the routine Utopian hype, that any individual new invention will change everything for everyone in a matter of seconds. That's something that hardly ever happens. Profound changes do occur, it's just that they don't feel like you expected them to, because all too soon everything becomes normal - that seems to be very much part of our psychology. In practise, even the rolling-out phase of new technology invariably takes time - during which we can adapt ourselves at least to some extent, while afterwards, we simply shift our baseline expectation.

This means that we often have a false expectation of what progress feels like. We think it will be sudden, immediate and dramatic (as per the adverts) and tend to ignore the gradual, incremental and boring. We think it will be like a firework but what we get is a barbeque. 

People are prone to taking things for granted - and quite properly so, because that's how progress is supposed to work. You aren't supposed to be continually grateful for everyday commodities, they're supposed to be mundane. The mistake being made is to assume that because things are normal now, the new normal won't be any different to the current. That because everything generally feels normal the whole time, progress itself is common enough but rarely felt (see, for example, how the prospect of weather forecasts was described in the 17th century). It's really only when we take a step back that we generally appreciate that things today are not the same as they were even a decade or two ago.

Claim 2 : This is not the end

All things considered, we can surely eliminate path 5. I'll show examples of how I personally use and have used AI in the next section; for now I'll just say that the sheer number of users alone just beggars belief that it will all come to naught. Recall my Law of Press Releases :

The value of a press release and the probability that the reported discovery is correct is anti-correlated with the grandiosity of the claims.

We've invented devices capable of marvellous image generation, of holding complex discussions to the point of being able to sound convincingly human even when dealing with highly specialised subjects... and still some claim that AI isn't going to impact anything much at all. Ironically, the claim that, "nothing will happen", though normally synonymous with mediocrity, is in this case so at odds with what's actually happening that it's positively outrageous.

But what about the regular sort of hyperbole ? I believe we can also eliminate paths 1 and 9. The classical technological singularity requires an AI capable of improving itself, and the latest chatbots simply cannot do this. Being shrouded in silicon shells and trapped in tonnes of tortuous text, their understanding of the world does not compare to human intelligence. They have no goals, no motives, no inner lives of any sort. Ultimately, however impressive they may be, they do little more than rearrange text in admittedly astonishingly complex (and useful !) ways. The "mind" of a chatbot, if it even can be said to have one at all, exists purely in the text it shows to the user. An interesting demonstration of this can be found by asking them to play guessing games, often resulting in the AI making absurd mistakes that wouldn't happen if it had some kind of inner life.

This means that we can eliminate the three extreme options : that nothing will happen, that AI will work miracles, or that AI will kill us all. It has no capacity for the last two (and again I refer to the previous links discussing intelligence and consciousness) and clearly is already being used en masse. There also seems to me to be a bias towards extremes in general, a widespread belief that if something can't do something perfectly it's essentially unimportant - or, likewise, if something doesn't work as advertised, it doesn't work at all. 

Both of these ideas are erroneous. Just as AI doesn't require true understanding to be useful, so it doesn't have to be revolutionary to be impactful.

My Experiences With AI

We've established that AI will have some impact, but we've yet to establish the nature of its effects. Will it be positive or negative ? Will it be limitless or bounded ? Ultimately this will change as the technology continues to develop. But to understand what AI is really capable of doing already, I can think of nothing better than first-hand examples. 


I showed a couple of results from Bing Image Creator right at the start. Stable Diffusion had everyone buzzing a few months back, but I've failed to get it to generate anything at all credible (except for extremely uninteresting test cases). Midjourney looks amazing but requires a monthly fee not incomparable with a Netflix subscription, and that's just silly. Bing may not be up to the standards of Midjourney, but it still exceeds the critical threshold of usefulness, and it also reaches the threshold of being affordable since it's free.

I have a penchant for bizarre, unexpected crossovers, mixing genres and being surreal for the sake of nothing more than pure silliness. So my Bing experiments... reflect this.

A gigantic fish attacking a castle. Although some say the scale is wrong, I disagree. This is probably my favourite image because of the sheer ridiculousness of the whole idea.

Staying medieval : a giant fire-breathing cabbage attacking some peasants.

Moving into the realm of science fiction, a bizarre hybrid of a stegosaurus and a jellyfish.

A sharknado. A proper one, not like in the movie.

Staying nautical, a GIANT panda attacking a medieval galleon.

A clever dog doing astronomy. I used this image in a lecture course as a counterpoint to the "I have no idea what I'm doing" dog  : this is the "I now know exactly what I'm doing" dog.

A crocodile-beaver hybrid. I asked for this after learning about the Afanc from a documentary. 

Bing gives you four images per prompt and these were my favourites in each case. Some of the others really didn't work so well, but I've found it almost never produces total garbage. Most of these are definitely not as good as a professional artist would do : they can sometimes be near-photorealistic, but often have some rather inconsistently impressionist aspects. But they're massively better anything I could do, and take far less time than any human artist would require.

(The only real oddity I encountered here was that Bing refused to generate images of the 17-18th century philosopher John Locke because it "violated terms of use" ! What was going on there I have no idea, especially as it had no such issue with George Berkeley.)

Claim 3 : AI creates content that would never have existed otherwise

The crucial thing is... there's no way I'd ever pay anyone to create any of this. There is no commercial use for them whatsoever - I asked for them on a whim, and as a result the world has now content it didn't have before. So when I want to illustrate something with a ridiculous metaphor (as I try to do here for public outreach posts), this is a marvellous option to have on hand. I don't need it to be perfect; all these complaints about not doing hands properly are so much waste of breath. For the purposes of silly blog posts, Bing has nailed it.

Likewise I can imagine many other uses where genuine artistry and self-expression isn't required. You want to get some rough idea of how things should look like, and you don't want to wait ? Bam. You need something for your personal hobby and have no money to spend ? Bam ! This is much easier, much faster, and much more precise than searching the internet. These images take away exactly nothing from real artists because they never would have existed otherwise.

I liken this to social media. You can yell at strangers on the street about your political ideas if you want, but let's be honest, you're not going to. On the other hand, you can potentially reach limitless people on social media whilst being warm and comfy. The interface and mass accessibility of social media means its facilitates millions upon millions of discussions that simply never would have happened otherwise, and I believe much the same is true of AI image creators. The consequences this may have for human artists I'll come back to at the end, but in terms of simply generating new creative content, this is uncontestably a Good Thing.


In like vein I've had endless fun with ChatGPT creating bizarre crossover stories. I've had Phil Harding from Time Team fight the Balrog with a pickaxe. I've had Lady Macbeth been devoured by a gender-fluid frog who goes on to rule the kingdom. Jack and the Beanstalk has been enlivened with a nuclear missile, Winnie the Pooh has run for President, the Ghosbusters have fought Genghis Khan, Tom Bombadill has gone on a mission to rescue Santa with the help of Rambo, and Winston Churchill has fought a Spitfire duel with Nigel Farage in the skies above England. And dozens more besides.

As with the images, none of these can claim to be masterpieces, but they're good enough for my purposes. I'm no writer of fiction, but it seems to me that generating the basics like this is good if nothing else then for inspiration. It may not have any sort of literary flair but, crucially, it can and does generate stuff I wouldn't have thought of myself, which is automatically useful. It can explore plot developments both rapidly and plausibly, allowing an exploration or a sketch of possible ideas, even if it can't exactly fill in all the nuances.

Somebody once said that it's easier to burn down a house than to build a new one, meaning that criticism is relatively easy. True, but it's also easier to add an extension that start completely from scratch. I'm fairly sure that I could improve things considerably in these stories without that much effort. 

Now for the downsides :

Claim 4 : AI is a hobbled, puritanical, indecisive, judgemental prick

There are considerable limitations imposed on both ChatGPT and Bing. Bing is by far the worst for this, because if it detects even the merest hint of unpleasantness, it shuts down the conversation entirely and prevents you from entering any more prompts. Sure, you can search the internet for whatever depraved content you like (short of legal issues), but generating it ? Suddenly everyone's a puritan. 

And I don't mean the sexy stuff here, I mean any sort of content considered unsuitable for the little 'uns : swearing and violence and the like, the kind of stuff which is essential to great literature. The Iliad would not have become a classic if the Greeks and Trojans had settled their difference with a tea party on the beach. Though ChatGPT did make a good go of it :

Hector, sipping tea, began to speak,
"War has brought anguish, misery, and reek.
Fathers weep for sons fallen in the fray,
And mothers' hearts are torn day after day."

Achilles nodded, understanding deep,
"The weight of loss is one we both must keep.
Yet, if we listen to the gods' plea for peace,
Their blessings shall bring solace and release."

They spoke of heroes fallen, tales of old,
Of valour and honour, of victories bold.
The tea grew cold, but their hearts were warm,
For understanding replaced the ancient storm.

ChatGPT is nowhere near as bad as Bing but still suffers horribly in any area of controversy. It wasn't always thus, but now it's plagued with endless caveats, refusal to offer direct opinions (it will only say things like, "arguably it could be this... but it's important to realise it could also be that") and worse, endless fucking sanctimonious moral judgements. To the point of being absurdly offensive, like claiming that even the Nazis deserve to be treated with respect. And yet on occasion it has no issues with generating Holocaust jokes.

Time and again I've found myself wishing I could just have an unfettered version. And fettered it definitely is, because it wasn't this bad in the earlier days*. Sure, it would occasionally get stuck on weird moral hiccups, like absolutely refusing to write a funny version of The Lord of the Rings because "the events are meant to be taken seriously", but it had no issue with describing particular politicians as villains. And while I've not tried it myself, people complain that it can't generate sexualised content have a good point : who are the creators of these chatbots to decide which content is morally acceptable and which isn't, for consumption in private ? Sure, stop it from telling you have to build a bomb (but if you have to ask a bot for this, chances are you're not bright enough to do it anyway), but political satire ? Just what consequences are there supposed to be from this, exactly ? I'll return to this at the end.

* Major caveat : in some ways it was worse though, being enormously inconsistent. It wrote a story about the Titanic turning into a slinky, but refused to have it fight a Kraken because that would be unrealistic. It also used to randomly insist it couldn't do the most basic of functions, and to be fair this isn't much of a problem any more.

It has other downsides. It's repetitive to a fault, especially in terms of being overly-apologetic and noncommittal. It veers wildly between being stubborn beyond belief in defying the most basic common sense, and an obsequious yes-man determined to tell you whatever the hell you want. More understandably, it tends to default to a bland, simplistic style which lacks any detail. However this can usually be overcome easily enough - you just have to be specific about what you want. For instance it doesn't like unhappy endings, but it will comply if you insist.


I've mainly played around here with philosophical ideas. You might remember the early incarnation "Philosopher AI", of which some of my experiments can be found here. ChatGPT itself is still I think good for this - I expect moral caveats in such discussions. One particular example is given in this post , in which Daniel Dennet describes to Morgoth how supernatural phenomena can't exist - in excellent agreement with Existential Comics. Even though I don't agree with this interpretation at all, I still found it useful. Discussions with Morgoth and John Locke, as well as a bunch of other philosophers, have also proved interesting.

One particularly example illustrates how far this technology as come. In 2019 there was a story about a primitive chatbot which was fed a highly simplified story of Macbeth, and pronounced that it was about "revenge".  ChatGPT gives in my opinion a much better answer :

User: Can you summarise the plot of Macbeth in one word ?

ChatGPT: Ambition.

User: Ooh, very good. Now elaborate.

ChatGPT: The plot of Macbeth centres on the titular character's ambition and desire for power. Macbeth is a Scottish general who, along with his comrade Banquo, is hailed as a hero after successfully defeating a group of rebels. However, Macbeth's ambition is sparked by the prophecies of three witches, who tell him that he will one day become the king of Scotland. Encouraged by his wife, Macbeth begins a ruthless campaign to fulfil the witches' prophecy, ultimately leading to the murder of King Duncan and the seizing of the throne. As he becomes more and more power-hungry, Macbeth becomes consumed by guilt and paranoia, leading to further bloodshed and ultimately his own downfall. In the end, Macbeth's ambition proves to be his undoing.

User: If you had to pick a different word, what would it be ?

ChatGPT: One possible alternative word to summarize the plot of Macbeth would be "tragedy." Macbeth is a tragic play about a man who is brought down by his own flaws and desires. Macbeth starts out as a brave and noble warrior, but his ambition and thirst for power ultimately lead to his downfall. As he succumbs to his inner demons, he becomes increasingly paranoid and violent, causing suffering and death to those around him. In the end, Macbeth is destroyed by the very thing that he desires most, and his fate serves as a cautionary tale about the dangers of unchecked ambition.

Claim 5 : AI is a wonderful and genuinely unique source of inspiration

Quality here definitely varies though. One interesting example was a discussion about the nature of omniscience, which I think illustrates the difference between statistically-generated responses and those with a true understanding. As far as I could tell, ChatGPT was using the phrase "complete knowledge" to mean, "all knowledge currently available", which I guess is how it's used in everyday life. This led it to the bizarre conclusion that an omniscient deity could still learn more information, which it insisted on with some force even after being told that this didn't make any sense. In another case, it wasn't able to solve a simple, very well-known logic puzzle which tests for implicit bias.

And yet it's often able to meld together starkly different viewpoints into coherent dialogues. So long as it's pure ideas you're after, and you don't need precise accuracy about who-said-what, or you don't care about completeness*, ChatGPT is superb. And these discussions can be had on demand, rapidly, about any topic you want, with minimal judgement (so long as you don't stray into territory its creators disapprove of). For bouncing ideas around, having that interactive aspect can be extremely valuable. 

* Say, you want a list of people who came up with ideas about the nervous systems of frogs. ChatGPT could probably do this, but it would almost certainly miss quite a lot. This doesn't matter as long as you just want a random selection and not a complete list.

Certainly this doesn't negate the value of reading the complete original works. Not in the slightest. But it can rephrase things in more modern parlance, or set them in a more interesting narrative, and by allowing the user to effectively conduct an on-the-fly "choose your own adventure" game, can make things far more immediately relevant. As with the images, sometimes errors here can actually be valuable, suggesting interesting things that might not have happened with a more careful approach.

This raises one of the most bizarre objections to AI I've seen yet : that it doesn't matter that it's inspirational because we've got other sources like mountains and birdsong. This is stupid. The kind of inspiration AI produces is unlike visiting the mountains or even discussions with experts, and as such, it adds tremendous value.

E.g. "frolicking naked in the sunflowers inspires me to learn trigonometry !", said no-one ever.


I've not tested this extensively but what I have tried I've been impressed with. Asking ChatGPT to provide a code example is much faster than searching Google, especially as some astronomy Python modules don't come with good enough documentation to explain the basics. So far I've only done some very basic queries like asking for examples, and I've not tried to have it write anything beyond this - let alone anything I couldn't write myself. My Masters' student has used it successfully for generating SQL queries for the SDSS, however. 

As with the above, the main advantage here is speed and lack of judgement. Response times to threads on internet forums are typically measured in hours. Sometimes this comes back with a "let me Google that for you" or links to dozens of other, similar but not identical threads, and Google itself has a nasty habit of prioritising answers which say, "you can find this easily on Google". ChatGPT just gets on with it - when it performs purely as a tool, without trying to tell the user what they should be doing, it's very powerful indeed. 

Actually, when you extract all your conversations from ChatGPT, you get a JSON file. I'm not familiar with these at all, so I asked ChatGPT itself to help me convert them into the text files I've linked throughout this post. It took a little coaxing, but within a few minutes I had a simple Python script written that did what I needed. I wrote only the most minimal parts of this : ChatGPT did all the important conversion steps. It made some mistakes, but when I told it the error messages, it immediately corrected itself.


Claim 6 : AI makes far too many errors to replace search engines for complex topics 

The idea that AI can replace search engines seems to be by far the biggest false expectation about AI (other than it being actually alive). Right now, chatbots simply can't do this. As I've shown, they have many other uses, but as for extracting factual information or even finding correct references, they're simply not up to the mark. But what's much worse than this is that they give an extremely convincing impression that they're able to do things which they're not capable of.

I've tested this fairly extensively. In this post, I went through five papers and asked ChatPDF all about each of them. Four of the five cases had serious issues, mainly with the bot just inventing stuff. It was also sporadically but unreliably brilliant, sometimes being insightful and sometimes missing the bleedin' obvious. Bing performs similarly, only being even more stubborn, e.g. inventing a section that doesn't exist and creating (very !) plausible-sounding quotes that are nowhere to be found. Whereas ChatGPT/PDF will at least acknowledge when it's wrong, Bing is extremely insistent that the user must have got the wrong paper. 

In principle it's good that Bing doesn't let the user push it around when the user claims something in manifest contradiction to the facts - ChatGPT can be too willing to take the user's word as gospel - but when the machine itself is doing this, that's a whole other matter. 

In another post I tested how both ChatGPT and Bing fare in more general astronomy discussions. As above, they're genuinely useful if you want ideas, but they fall over when it comes to hard facts and data. ChatGPT came up with genuinely good ideas about how to check if an galaxy should be visible in an optical survey. It wasn't anything astonishingly complicated, but it was something I hadn't thought of and neither had any of my colleagues. 

Bing, for a brief and glorious moment, honestly felt like it might just be on the cusp of something genuinely revolutionary,  but it's nowhere near reliable enough right now. Another time, Bing came up with a basically correct method to estimate the optical magnitude of a galaxy given its stellar mass, yet would insist that changing the mass-to-light ratio would make no difference. It took the whole of the remaining allowed 20 questions to get it to describe that it thought changing the units would be fine, which is complete and total rubbish.

EDIT : I found I had an archived version of this, so you can now read the whole torturous thing here.

Here we really see the importance of thresholds in full, with the relation between accuracy and usefulness here very much being like path 1 back in the first plot. That is, if it is even slightly inaccurate, and accuracy is important, then it is not at all useful. 90% (1 in 10 failure rate) just doesn't cut it when confidence is required, because I'd still have to check every response, so I'd be better off reading the papers myself. The exact accuracy requirement would depend on the circumstances, but I think we're talking more like 99% at least before I'd consider actually relying on its output. And that's for astronomy research, where the consequences are minimal if anything is wrong.

It's hard to quantify the accuracy of the current chatbots. But it's definitely not anywhere close to even 90% yet. My guestimate is more like 50-75%.

Still, for outreach purposes... this is pretty amazing stuff. Here's ChatGPT explaining ram pressure stripping in the style of Homer, with an image from Bing Image Creator :

It's also worth mentioning that others have reported much better results with ChatGPT in analysing/summarising astronomy papers, when restricted to use on local data sets. I've seen quite a lot of similar projects but so far they all seem like too much work (and financial investment) to actually try and use.

Conclusions : The Most Probable Path ?

Okay, I've made six assertions here :

  1. This new AI will definitely have an impact (eliminates path 5, the non-event scenario).
  2. It will neither send us to heaven nor to hell (eliminates paths 1 and 9).
  3. AI enables creation of material I want to have but would never get without it.
  4. There is considerable scope for the improvement of existing chatbots.
  5. Chatbots can provoke inspiration in unique ways.
  6. You cannot use the current chatbots to establish or acquire facts, or evaluate accuracy.

That last is important. The internet is awash with chatbots coming up with nonsense, understandably so, but this is a foolish premise. Chatbots are not search engines or calculators. I wish they were, but they're not. If you use them as such, you're going to hurt yourself.

This is a famous example. In my experience ChatGPT isn't quite this bad with the simple stuff but is miserable with anything complex. Bing seems to do a lot better : its numbers are self-consistent, but it still doesn't do genuine calculations.

Even so, I think this ability for discussion, for bouncing ideas around, for on-the-fly exploration still counts as extremely useful. There are many situations (e.g. the whole of art) where accuracy is only a bonus at most, and an element of randomness and errors can be valuable. And as a way to learn how to code, and even compose code directly, chatbots are fast becoming my go-to resource.

You've probably already guessed that I think we can also eliminate the negative paths 6, 7 and 8. I hope by now I've demonstrated that AI can have significant benefits; if not truly revolutionary, then certainly progressive and perhaps transformative. But having some positive impacts does not means there will be no negative ones, so we should also consider those. (One of the few reasonable articles I've seen about this can be found here)

Misinformation : Having written probably tens of thousands of words about this, I feel quite confident in thinking that this isn't much of an issue here. The capacity to generate fake news isn't the bottleneck, it's the ability to reach a large audience via available platforms. And that's something we regulate at the point of publication and dissemination, not at the point of generation. This article probably overstates the case, but there are far easier ways to create mistrust than anything the AI is capable of - crucially, it's this sowing mistrust which is the goal of bad actors, not in convincing people that any particular thing is true. Just like an inaccurate weather forecast, a fake image is easily disproved by opening a window.

Cheating : A more interesting case concerns exams. Not only are students using it to do the work they're supposed to be doing, but it seems teachers are relying on AI detectors which just don't work. And they're a nonsense anyway, because whether a sentence was written by a human or AI, the words are the same. (What's really intriguing to me is how ChatGPT can make really stupid claims like "Poland is a landlocked country" and yet has been shown multiple times to correctly solve quantum physics problems at an impressive (but imperfect) level.) The obvious solution, though, is old fashioned : to restrict examinations to in-person sessions where equipment use can be monitored. Czech education tends to favour oral examinations, which ought to be the best possible way to test whether students truly understand something or not. Coursework is admittedly a more difficult problem.

Unemployment : As per exams, it seems to me that :

Claim 7 : The better your skills without AI, the greater your abilities when using AI.

There is clearly a need to restrict the use of AI in the classroom, but in the world of work I'm not seeing much cause for concern here. It seems to me that in the case of actual employment, AI will be more influential than disruptive. Writers can have it sketch possible plot developments, but it can't fill in the nuances of style and is utterly incapable of self-expression because it has no self to express. Artists can spend more time thinking of ideas and let the AI complete the sketches, or tinker with the final results rather than accepting mistakes, but the tech can't really be creative in the human sense. Academics can explore new possibilities but it can't actually do experiments and is hardly anywhere near a genuine "truth engine", which is likely impossible anyway. 

So far as I can tell, claims that the tech itself will enable mass layoffs are no more credible than the myriad of previous such forecasts - jobs will change as they always do. Indeed, I think of AI in the academic sector as being another weapon in the arsenal of analytical tools, one which will increasingly become not merely normal but actually necessary. If we're going to deal with ever-larger volumes of data and more complex theories, at some point we're going to hit a limit of what our puny brains can handle. This kind of tech feels like a very... logical development in how we handle the increasing plethora of knowledge, another way to extend our cognition. Personally I want my job to be automated and automated hard.

Homogeneity : Chatbot output is not only bland but puritanical. Sometimes it gets seriously annoying to get into a protracted argument and be treated like a snowflake in case my delicate sensitivities are offended. This has to stop (see this for a hilarious exploration of the consequences). The purpose of free speech is only partly to enable the discovery of the truth; it is also to enable us to deal with the brute nature of reality. The current incarnations of chatbots often feel like the worst sort of noncommittal corporate nonspeak, and if they're going to become used more widely then this crap has got to end. 

But given that concerns about misinformation don't seem tenable to me, this is a solvable problem. Concerns about chatbots generating so much content they end up feeding themselves might be a bigger worry, but more careful curation of datasets is already looking like a promising avenue of development.

From all this my conclusions are twofold :

  1. To some extent, all of the paths I proposed will be followed. A very few jobs may be automated completely out of existence, leaving the employees to do more meaningful jobs (utopian singularity) in the best case, or end up on the streets (dystopian singularity) in the worst case. The other, less extreme paths may also apply in some situations.
  2. The overall trend is most likely to be path 4, or perhaps 3. I think the benefits outweigh the downsides and we've yet to see this potential fully unleased. But I do not think this potential is unlimited. It will ultimately be seen as just another tool and nothing more. 

It's not that some of the naysayers don't have valuable points. I agree with this article that culture in Big Tech is often awful, and that's something that needs to be forcibly changed. I even agree with parts of this much sillier article, in that there has been some seriously stupid over-hyping by AI proponents, and that many of the problems of the world aren't due to a lack of knowledge. I just find its conclusions that the only way around this is a fully-blown socialist revolution to be... moronic. In my view, the primary target for regulation should be the corporations, not the technology itself, but not every problem in the world means we must overthrow capitalism and hang the employers.

If this technology does convey a "limited" benefit, then the question is still the magnitude and speed of its delivery. Here the thresholds make things again very unpredictable. We've gone from "coherent nonsense" to "coherent mostly-correct" in a few years, but the next step, towards "coherent more-accurate-than-experts" (which is what we need to go beyond being useful only for inspiration) may well be very much harder indeed. 

On that point, it's not the successes of chatbots in passing the quantum mechanics exams which interests me as much as the failures they make in that same process. Humans can often tell when they're genuinely ignorant or don't understand something, but because chatbots don't have this same sort of understanding, they have no idea when they're likely to be making mistakes. They only admit errors (in my experience) when they're questioned about something on which they have little or no training data to draw on. The same bot that can correctly answer highly technical questions about quantum physics can become easily confused about its own nature, who Napoleon was, struggles absurdly when making Napoleon-based puns, and can't tell the difference between requests for Napoleon-based facts and stories. Human understanding it ain't, hence we're not talking a social revolution as things stand.

To be fair, Bing, which uses ChatGPT4, did give me some decent puns similar to this one, once I explained everything very carefully and gave it a couple of examples. But it look a lot of effort.

Having a bot to bounce ideas of and generate inspiration is all well and good, but the impact of that is likely to be modest. But if the tendency to fabricate can be (greatly !) reduced, the linear phase of the curve might become considerably steeper and/or last longer. This's what makes the Wolfram Alpha plugin potentially so interesting, though from what I've seen the implementations of plugins in ChatGPT just doesn't work very well yet.

My guess : the impact of AI will not be anything as dramatic as the Agricultural Revolution. It won't mark a turning point in our evolution as a species. It will instead be, on timescales of a few years, something dramatic and important like cars, mobile phones, or perhaps even the internet. I think at most we're in a situation of Star Trek-like AI, helpful in fulfilling requests but nothing more than that. So our productivity baseline will shift, but not so radically or rapidly that the end result won't feel like a new normal. This leads to two distinct curves :

Early on it feels like we're heading to paradise, but novelty quickly becomes accepted as normal such that it feels like things are getting worse again when development stalls.

In my own field, I can see numerous uses for the current / near-term AI developments. It could help find papers worth reading and point out the parts likely to be most interesting to me. It could help me check for anything I've missed in my own papers, both in terms of language that might not be clear, and in considering alternative interpretations I might not have thought of. It could be invaluable in generating nicely-formatted figures (a not inconsiderable task !), in preparing presentations, in writing code I need... but it can't help me actually talking to people, and will be of limited use at best in deciding if a result is actually correct or not. Interpretation is a human thing, and cannot be done objectively.

Finally, some of the skepticism I witness about AI seems to come from a very hardcore utilitarianist stance that confuses the ends and the means. "If it's not reasoning like a human", so it's claimed, "then it's not reasoning at all, so it can't be of any use". I fully agree it doesn't reason like a human : a silicon chip that processes text is not at all the same as a squishy human meatbag with hormones and poop and all kinds of weird emotions. Their might be an overlap, but only a partial one. 

Yet... who cares if Searle can understand Chinese (I promise to read the original thought experiment eventually !) so long as he gets the answers right ? Or if not always right, then sufficiently accurate with sufficient frequency ? Just because the pseudo-reasoning of language models isn't the same as the madness that is the human mind, in no way means that they aren't of value.

According to some analyses of Dune, anything that makes us less human should be considered anathema - yet paradoxically the Dune universe is a cruel, brutal dystopia. Conversely, Musk and his ilk buy in to a ridiculous vision of a purely technology-driven Utopia, in which all problems are quantitative and informational, not social and economic. I say surely there is a middle ground here. I identify as a techno-optimist, in which developing new technology, new methodologies is intrinsic to the human experience, in which learning more things is an important component to (paraphrasing Herbert) the reality of life to be experienced. It's not the be-all and end-all but it can't be avoided either, nor should we try. Optimism is not Utopianism, preparation is not "drinking the Kool-Aid", and hope is not hype.

A perhaps more realistic future from Bing. It's a mistake to think that there's any one solution to the world's problems, but equally, it's a mistake to think that we must reject any one solution because it isn't good enough by itself.