Big Digital Tech Moves Into Synthetic Biology: The Generative AI Rush/Black Box Biotech - Pt 1/2

[Music] hello and welcome I'm Lyn freeze producer of global political economy or GP newss today's segment will focus on AI generative biology and why this new approach to biotechnology raises serious challenges for the convention on biological diversity this featured comments by Jim Thomas the key message being the integration of artificial intelligence with synthetic biology under the control of the world's largest and best capitalized companies is a recipe for real problems down the line problems ranging from adverse and unexpected impacts on health economies on biodiversity in the longer term once a greater variety of Engineers proteins make it into the market our bodies and the biosphere as argued by Jim Thomas in his report DNA the artificial intelligence artificial life convergence the world's regulators and governments responsible for oversight of biotechnology have the chance to apply the precautionary principle before the number of Novel protein entities entering the biosphere starts to mimic the toxic trajectory of synthetic chemicals on that trajectory as reported by scientists in early 20202 humans have breached the safe planetary boundaries for novel chemical entities in the biosphere to press points made by Thomas it was from the enormous challenge of trying to deal with the negative effects of unassessed poorly understood synthetic chemicals that the precautionary principle was first established in environmental governments this principle roughly states that it's appropriate and prudent to take early action to prevent regulate and control an emerging threat before we have all the data to conclude on its exact nature the precautionary principle was crafted exactly to try to prevent highly disrupted technological developments running into widespread application ahead of proper oversight and governance the precautionary principle is enshrined in the UN convention on biological diversity and the caragana protocol on bios safety it's this core principle that's guided the convention on biological diversity in meeting its ecological and socioeconomic objectives including assessment of potential threats to livelihoods the sustainable use of biodiversity and ethical and cultural considerations since establish in 1992 at the UN Rio Earth Summit the convention on biological diversity and its protocols has served as the world's Premier Global instrument for oversight of biotechnology the vast majority of the world's governments have adopted the treaty and are called the parties to the UN convention on biological diversity and when these parties meet that's called the conference of the parties and this is the Supreme decision-making body of the convention on biological diversity the next conference uh cop for short uh will be uh held from the 21st of October to the 1st of November in col Colombia to further clarify all this when you hear reference to cop 16 of the CBD what that's referring to is the 16th meeting of the conference of the parties to the convention on biological diversity in the leadup to the upcoming CBDs C 16 the African Center for biodiversity together with third world Network and Etc group produced blackbox biotech a new report on generative biology the report was researched and written by Jim Thomas and serves as a briefing paper ahead of the CBD cop 16 under the offices of the African Center for biodiversity third world Network and ET C group the report was published on September 3rd followed by an online webinar on September 12th as further briefing ahead of the cbd's cop 16 titled blackbox biotech the online briefing featured five speakers and was moderated by the African Center for biodiversity the online briefing announcement provided an overview as follows the United Nations convention on biological diversity has for 30 years governed new developments in biotechnology in the frame of precaution and Justice and has also recently established a process of Technology Horizon scanning assessment and monitoring of new developments now there's an industrial attempt to converge Next Generation genetic engineering tools synthetic biology with generative artificial intelligence or AI of the sort used by chat GPT in a new generative biology industry on the agenda of the blackbox biotech briefing was why the cbd's expert groups propose an urgent assessment of this newest AI biotech convergence how the use of generative AI in biology brings thorny new problems steming from the opaque and aerone blackbox character of generative AI how the world's largest digital tech company ianes are fueling a generative biology Rush including a bold biopiracy grab of all the world's digital sequence information on genomic resources and what can be done at cop 16 in ki Colombia so this segment as noted at the open will feature comments on all this by Jim Thomas of special relevance to today's segment on generative biology Thomas was a member of the multidisiplinary ad hoc technical expert group on synthetic biology established by the conference of the parties to the UN convention on biological diversity he has almost three decades of experience tracking emerging Technologies ecological change biodiversity and food systems on behalf of movements and in un fora Jim Thomas' homepage is ww. scanth horizon.org where he posts on his current engagements as researcher writer and strategist prior to this he shared the work of the ETC group where he was co-executive director and research director so we go now to our future clip now without further Ado I would like to now welcome our first Speaker Jim Thomas whose bio has already been posted in the chat uh we won't read bios uh because of time now Jim Please welcome and uh please share your screen and start off with the presentation great and I hope everybody can see my slides as Sabrina says it's my task here to present this new briefing blackbox biotech which is a you know a sort of short introduction to the question of the integration of artificial intelligence and synthetic biology what's being called generative biology and I really do want to thank this African Center for biodiversity who who really show great foresight in in commissioning this work along with ET group and and third world Network um and also the reviewers uh particularly um Dr Maya montro of UC Santa Cruz um and Dr Dan millin from Goldsmith's College in London um one thing I I would really like to emphasize is that this this this report is just a briefing it's an introduction it's a sort of a preliminary scan of the issues that are raised and and that's because there isn't yet a a deep dive significant uh report that's looked at the many policy issues Equity issues sustainability issues that are now raised by these new developments in so-called generative biology and there urgently needs to be that um and such a such a study needs to happen under the ages of uh trusted uh International bodies such as the convention on biological diversity um and luckily that's exactly the option that's uh in front of the conference of the parties the 16th Conference of the parties in in car next month uh the option to actually commission an in-depth assessment on the potential impacts of the integration of artificial intelligence machine learning into synthetic biology this is something that's urgently needed the these Tech this technology this integration is moving very fast into commercial use for those who may not know some of these terms synthetic biology is is a term that's used to broadly describe the Next Generation techniques and approaches to genetic engineering it tends to refer to more experimental approaches and newly emerging Technologies and honestly is very often a sort of a hype term that mobilizes capital and and investment um but also research agendas and the underlying concept behind synthetic biology is to try to make the the the somewhat messy world of bi ology more predictable more rational more of an engineering substrate programmable even and so there's a lot of metaphors in the field of synthetic biology like programming DNA as code or life as machines which make strong powerful metaphors but are problematic in terms of uh of obscuring the some of the complexities and and and messiness of of Living World um and uh and and and of course because this is a term that's often used for mobilizing money there's there's a tremendous amount of hype we're talking about techniques such as genome editing synthesizing new DNA and RNA or proteins and so forth if the field of synthetic biology um is full of hype and obscuring metaphors then even more so the topic of artificial intelligence and I think it's important to recognize that artificial intelligence as a term covers a whole bask of computational Technologies used for data analytics forecasting natural language processing and so forth and most importantly what we're not talking about here is the science fiction version of of artificial intelligence this is not thinking machines intelligent computers computer sentients um what today passes for artificial intelligence is sets of computation that calculate probabilities and then make sort of predictions um and and they're often trained on extremely large sets of data that are then interrogated in order to make these kind of predictions there are different types of artificial intelligence I'm not going to talk about traditional AI um discriminative AI is is the sort of AI system that takes large amounts of unstructured data and is able to look within it and sort of recognize patterns uh for example to look at pictures and recognize that there's a cap there and generative AI which is much of what we're going to be talking about also depends upon taking large large sets of data um and then building a model uh which can generate similar types of data basically um this is the kind of AI that you have that says not not recognize a cat but draw me a picture of a cat or write me an article about a cat and creates synthetic data in a predictive way rather in the way you're phone phone will make predictive text it will try and work out what you want and present it to you the reason why generative AI is so much to the four is that there is a massive investment boom right now around these generative AI systems really sparked by the um the coming out of uh chat GPT at the end of 2022 now we see hundreds of billions of dollars being sunk into the generative AI space um with with the Hope by investors that they're going to get very real outcomes here um so far and we we've seen Goldman Sachs and others point out these hundreds of of billions of dollars are are really not yielding anything very much and so there's a Hope by moving into synthetic biology and other areas they'll they'll yield a bit more um in the in the report uh we we lay out four different areas where artificial intelligence is is combining with synthetic biology and biotech and I'm going to focus mostly on the first of these generative biology the use of artificial intelligence for biodesign and what we're talking about here is asking uh an artificial intelligence model to come up with new strands of DNA or new protein sequences um that might not have existed before and I'll talk more about that in a moment but it's worth noting also um use of arcial intelligence can improve Machine Vision and laboratory processes or or fermentation in bioproduction that we're seeing for example in um digital agriculture the uh the combination of of living organisms being modified alongside uh Ai and that's we call biodigital Convergence um and we're even seeing uh artificial intelligence computation being carried out at a at a experimental way in living cells for example brain organoids so so there's there's a biocomputation part to this biodesign and generative biology um which is mostly what we're going to be talking about sits on a very simple idea if you use chat GPT you'll know that that's a AI model which is trained on Millions even billions of pieces of text uh such that you can say to it write me a poem about a dog and it will write you what looks like a poem about a dog or you can get something like mid journey and you can say draw me a picture of a dog and it will draw on the millions of images that it's been trained on to draw you a picture of a dog um and so the idea of you can take one of these generative AI models and train them on millions of digital sequence information about genetic resources on DNA and RNA then you can also say design me a protein and as Jason Kelly here of Ginko bioworks puts it the idea is to make an AI model that can speak protein or speak DNA just like chat GPT speaks English the poster child for this the sort of proof of principle is a program that that's very high-profile called Alpha fold developed by Deep Mind which is Google's AI uh section and in about 2017 2018 uh Alpha fold was trained on on many thousands or ultimately hundreds of thousands of uh sequences protein synquis um the the the the sequence that um uh of RNA that is then folded into uh into a into a living protein and by 2021 uh Deep Mind were claiming that Alpha fold could could work out how every single protein that is known every protein sequence folds into actual proteins and this the solved supposedly what is called the the protein folding problem in biology um that an AI was able to do what what takes uh many years for a human scientist to do and and this was really held up as a as a major Leap Forward for um uh for big science and and for AI driven biotechnology um the the excitement of a Google Alpha fold is is also about the fact that now we can get an AI to to begin to control or or predict the Living World at the molecular level um but it's it's worth raising a bit of a red flag here while there's a lot of excitement at the lab bench protein scientists are saying well wait a minute these are just predictions um as is true of much of AI this this has to be checked and in fact we're seeing a large number of errors in what Alpha fold is is predic um and and limits and even hallucinations which I'll come to soon and so Alpha fold even though it's held up as this this wonderful um example of of using AI to solve biological problems actually was very much overclaimed and this is something we've seen whether it's with Gene editing or even um generative AI these an instant over claims and and then need to sort of row back on that one metaphor that we've leaned on heavily in this briefing and it's important to understand if you're not familiar with the with uh debates around artificial intelligence is the concept of the blackbox um basically um the blackbox problem which is much discussed in AI policy uh refers to the fact that uh uh when you train an AI model um and then it makes outputs and decisions it does so sort of hidden away in a black box it's not possible to understand why it made decisions that it made it's just simply too complex um and the blackbox problem of not being able to have explainability this opaqueness causes uh real problems for policy and and in this case for outcomes it has it means that humans have been cut out of the loop on decision making and deciding why particular genetic sequences are used um it has serious implications for safety and accountability and traceability and I'll come back to that in a moment another common Topic in AI policy that's very relevant here is the notion of hallucinations um and this is when you have uh an AI model uh for example supposed to produce images and those images look okay but when you look closely at them you find that they have all sorts of errors or AI text that is full of Errors so here we have uh an old man who when you look closely has impossibly long right arm and six digits on his hand being impaled by a unicorn this is because of a hallucination by the by the AI image system um and analysts have estimated that AI systems will hallucinate about a third of the time and about half the time there's some kind of error within their results um this is quite significant and um it's it's significant when you're talking about text and images it becomes extremely important if You' got hallucinations occurring in living organisms or or within uh biological molecules Scholars have pointed out that this isn't this isn't the system not working properly this is the system working properly and this is actually baked into how AI generative AI works and have suggested that generative AI systems should be scientifically classified as machines they just make something that kind of looks right but they're not fundamentally interested in finding truth there are also very serious issues around bias and that we refer to in the report and that has to be brought into considering the use of AI for um building synthetic organisms in the report we touch on some of the some of the biological molecules that are that AI systems generative AI systems are now being asked to generate these are novel biological molecules new synthetic proteins that would never have existed before in nature new strands of DNA and RNA and and each time the decision making on how to order those those genetic codes or those protein codes is hidden it's hidden in the Black Box there's also companies that are building new Gene editing proteins people will be familiar with crisper cast 9 as a system but the there are companies like proin who are now creating new AI generated Gene editing systems or indeed ways of uh changing the epigenetics uh things like histone modification the ways in which uh genetic systems Express themselves that's also being redesigned through artificial intelligence one of the things we focus on in this this short report is is how much big Tech big um big digital Tech is embracing this shift to putting together artificial intelligence and synthetic biology uh a recent high-profile book on artificial intelligence by Mustafa saliman um who was in fact the uh one of the founders of Deep Mind um and is now the head of Microsoft AI uh really is focused on this question of how artificial intelligence and synthetic biology are creating as he says one of the most profound moments in history well well that's a lot of hype but it is significant and we're seeing some clusters of um of work by very large digital tech companies Google of course because of their work on deep mind uh on on uh Alpha fold have their own generative biology company called isomorphic Labs um but are also working with probably the leading synthetic biology company gko W bioworks to produce synthetic versions of flavors and fragrances and food ingredients Microsoft have their Microsoft GPT platform and open AI which is largely owned by Microsoft is working with Los alos lab on these issues Amazon um is also working with uh a generative biology company called evolutionary scale and they have a model called esm3 but inter ly the Bezos Earth fund which by amson founder Jeff Bezos has put aund millionar into using artificial intelligence for climate and nature but largely focused on synthesizing proteins for food and other companies such as Nvidia Salesforce meta tensent Alibaba these are literally the world's largest and best capitalized companies who are all going fully into this area so I wanted to to end by by touching on five urgent Challen Alles that this this commercial rush into generative biology raises and I was part of the multidisciplinary ad hoc technical expert group on synthetic biology that began to look at this topic earlier this year and very quickly the issues that that group started to identify were about bios safety um of course if you're producing uh new DNA strands and so forth that have hallucinations in it then then we have then we have a worry about safety but in fact many on that group who were bios safety assessors pointed out that as assessors if the uh if if the decision making over how to make these new uh proteins and and DNA was done in a black box they have no data to work with to do safety assessments and that's very significant so the black box is obscuring the ability to do bios safety assessment um the military planners have also pointed to something called the pacing problem uh briefly uh in the same way we're now seeing um large amounts of synthetic pictures and text coming out of chat GPT that's overwhelming the internet what happens when we start to see large amounts of synthetic early produced artificial intelligence designed living organisms uh that uh May overwhelm bios safety Regulators probably the issue that I found most concerning however was this it was about biopiracy um as I've mentioned in passing in order to have these models you first have to train them on massive amounts of what is called digital sequence information um a company like Nvidia here there's a quote from Nvidia saying that for their gen slm platform they took all the DNA data for DNA and RNA data for viruses and bacteria about 110 million genomes learned a language model over that and can now ask it to generate new genomes for profit um that's a massive utilization of digital genetic sequences um and because this is all done in a black box there's no traceability back to which sequences are being drawn on to create the new genomic sequences protein sequences and so forth um you've lost traceability you have this massive utilization for commercial uses and this gets away from the core the core principle that the convention on biological diversity has worked on the idea of fair and Equitable access and benefit sharing the idea that we we we Trace where uh genetic sequences come from and then when they're used for commercial and other purposes there are benefits go back to those original stewards of biodiversity um by having this in a black box that's lost and and just to just to emphasize every single one of these models requires that massive amounts of data is is training this genetic sequences and that massive amount of data is increasing we now have companies I think there may be people here from base camp research who who are now trying to get new genetic sequences to enlarge the amount of data going in so so this is very important um we're going to hear a lot of promises around the fact that uh the use of generative biology could create new drugs new proteins for so-called sustainable food stuffs for sustainable biomaterials and that this may help the sustainable use of biodiversity to reduce fossil fuel uses and so forth but that has to be put in context these systems these generative AI systems are are incredibly energy hungry the computation required um at the moment is using up energy on the scale of say the country of Sweden electricity but also massive water use which of course is being extracted from agricultural systems and so forth and of course massive use of minerals silicon copper and so forth um and so it we maybe at the end of the day we find that use of those systems actually puts too much pressure on biodiversity there are concerns about how you canot just produce uh new Plastics or new drugs but you can also produce new viruses and new toxins and and this has to be dealt with through uh the biotechnology but the weapons convention and finally you know one of the core tasks of the convention on biological diversity is the commitment to respect preserve and maintain the knowledge the Innovations and practices of indigenous and local communities um much of what is being promised on the Promises side is to be able to make new sweeteners new proteins new flavors new fragrances and these will directly replace um those that have been stewarded by grown by looked after by um indigenous peoples and local communities and change the underlying um uh economies that that these communities depend upon um I'm going to leave it there others will have important things to say and I really encourage you to look at this new report uh on the AC bio website thanks very much so that gives us a picture of the generative biology rush and the serious challenges it raises for the UN convention on biological diversity over the long term and immediately this October 21st to November 1st at the convention of the party's 16th meeting cop 16 the question being will the current Raj of big technology companies investment and hype around generative biology and the use of AI to boost biotechnology production Prevail over biotech and biodiversity policymaking at the gbt conference of the parties or cop 16 of the CBD will parties follow the recommendations of the convention on biodiversity technical expert Group by which as put in the report parties have a very clear and straightforward opportunity to prevent the issues of generative biology from upturning and hollowing out the Decades of good work that the convention on biological diversity has led to help establish good governance over biotechnology the point being as put in the report the CBD needs to find answers to at least the following questions one does AI generative biology undermine access and benefit sharing Arrangements of the ngoya protocol and the governance of digital sequence information two does AI generative biology undermine biosafety Arrangements of the cogena protocol on biosafety three does AI generative biology pose biocurity bioweapons risks four will the integration of artificial intelligence with synthetic biology improve or woren health and sustainability and five what are the implications of AI sinmo integration for traditional knowledge and practices with the benefit of this briefing in the leadup to cop 16 of the CBD hopefully we all will now be able to separate hype from reality in news and Analysis of all this especially as the outcome of this 16th Conference of the parties to the convention on biological diversity becomes a news item with it the conclusion of cop 16 on Friday November 1st and this concludes today's segment from GP newss thank you for your interest this video documentation has been adapted from original recording of the September 12th 24 online briefing courtesy of the African Center for biodiversity

2024-10-15 02:14

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