In the heart of Switzerland, not too far from the Reichenbach Falls, by the way, where Sherlock Holmes defeated Professor Moriarty (more on that later), lies the Federal Government’s Spiez Laboratory, whose specialty is the study of deadly toxins and infectious diseases () in The Last Problem”.
Nine months ago, scientists at the lab conducted an experiment using their artificial intelligence-driven drug discovery platform called MegaSyn to study how it might work if it weren’t tied to its usual parameters. Like many AI platforms, MegaSyn relies on a large database (in this case, public databases of molecular structures and associated bioactivity data) that it typically uses to learn how to put new molecular combinations together to speed drug discovery. The rationale is that MegaSyn can avoid toxicity in molecules and thus screen out “good” ones.
In the Spiez experiment, MegaSyn was not constrained by the need to get good results, and after running overnight, it produced nearly 40,000 designs of potentially deadly standard bioweapon combinations (some as deadly as VX). It is an excellent example of machines that are not constrained by morality (humans have voluntarily crossed that moral threshold) and achieve very negative results.
Another recent example is the reported conversation between Blake Lemoine, a Google
Shockingly, there is already a lot of evidence that AI plays a military role. In Ukraine, drones have been programmed to detect and attack Russian military equipment. Larger nations can use AI for weapon systems to make them seek and destroy their enemy, and having seen the impact of drone technology in the Nagorno-Karabakh war, we may not be far from an AI-driven war .
This example, and the broader emerging debate about AI, gives us a sense that there are multiple complex axes in the emerging new world order. For example, there is a lot of talk about the growing strategic rivalry between the US and China, and some of that rivalry will certainly center on AI – in terms of computing power and access to large public and private datasets (Europe is ahead of the US when it comes to curbing the use of data in AI). Within these large regions will be another line of tension between people and the impact that AI is having on their lives (e.g. on minorities).
US vs China
It’s not all negative, however. In a widely publicized experiment last week, a project called Democratic AI allocated the outcomes of an investment game in a way that was more egalitarian than the outcomes chosen by purely human actors. It suggests that while the research benefits (and dangers) of AI are more tangible in settings like biotechnology, there are also very clear policy outcomes (for democracy and public policy).
At this point, it’s fair to say that most governments are falling far short of what they need to understand and better understand the impact of AI on our lives (from insurance policies to airfare to the interaction between social media and politics). . While I can’t claim to have any clear insight myself, I can recommend a few decent resources – the state of the AI report, Kai-Fu Lee and Quifan Chen’s book AI 2041, not to mention the entertaining The Love Maker.
Now back to Moriarty, another man with dark dreams of becoming ‘king of the world’. Rumor has it that one of the people who inspired Arthur Conan Doyle’s characterization of Moriarty was George Boole, Professor of Mathematics at University College Cork since 1849. Boole, one of the great mathematicians, created Boolean algebra, which laid the foundations for computer language and is the structure around which scientists deploy machines to mimic and “improve” human behavior.
I spent years in the basement of the UCC Boole library slaving away with AI – although I didn’t know it at the time. The stupid thing is that it was called regression analysis back then, the data sets were very, very limited and the computing power from today’s perspective prehistoric (See my account).
If I had known the regression caterpillar would turn into an AI butterfly, I might have stuck with it. My lesson is that computing power and, in certain cases, datasets will continue to improve, pushing the boundaries of law, moral philosophy and strategic competition between major regions.
Time to bring Sherlock back!