Ai, Y-Ai, Y-Ai -They’re Here!

Privacy?! Personal financial information? Exceptionally personal information? Lots of legislation to protect consumers from hacking and revealing their most intimate secrets? Powerful companies supporting a level playing field as to access to information and implement commercial transactions and trades? LOLOLOLOLOLOLOL. What are you smoking? We live in a world of accelerating artificial intelligence (AI) – software that enables high speed computers to assimilate vast pools of big data, learn all possible combinations and trends asked of them, and able to learn and reprogram themselves – all while using supercomputers. Snail computers compared to what will happen when quantum computing come online… just around the corner. There is too much tempting personal information out there, stuff that can generate billions and billions of dollars a year in additional profits, no matter the statutory and regulatory risks.

We cannot forget that Wall Street is always looking for shortcuts, advantages, fast-tracks, real-time analysis of massive data perhaps with automated decision-making (programmed trading on steroids)… even to the point of shortening the physical path between computer and data inputs, across long distances and even within data centers themselves. Let’s look at the efforts emanating from Wall Street when it comes to AI. Nanoseconds matter. 

Wall Street is on a hiring binge for academics and AI specialists to generate the next generation of financial tools based on AI. And getting, configuring and collating data for AI is hideously expensive. The fastest computers, the least expensive part, are also outrageously expensive. The advantage is staggering to those with the resources to build AI business units and deploy the best minds to create strategic capacities not even possible just a year ago. The playing field would be so tilted as to slide all but the richest financial institutions right off the table. But with that computing power comes unbridled financial, economic and, inevitably, political power.

While scientific and medical research, infrastructure maximization and energy allocation are and will be beneficiaries of this technology leap, the potential damages (from glitches to job displacement) have yet to be fully appreciated. If hacks and glitches have been nasty to date, with these high-speed autonomous systems, risks are amplified and multiplied thousands of times over… when mistakes can penetrate a system and spread much more rapidly than we have ever seen before. “Financial technology start-ups have begun using machine-learning algorithms to model credit ratings and detect fraud. And hedge funds and high-frequency traders are using AI to make investment decisions.

“Politicians are starting to take notice. In mid-October, the newly formed Task Force on Artificial Intelligence of the House Financial Service Committee held hearings on how AI could raise data privacy concerns in the financial industry. In June, Sen. Elizabeth Warren called on federal regulators to crack down on ‘algorithmic discrimination’ by financial institutions, noting that financial technology companies often charge minorities higher interest rates.

“Artificial intelligence also could fundamentally change the way that our financial system works. And until we understand how those changes could play out, we will be ill-equipped to deal with them.

“In the last decade, the broader field of artificial intelligence has made remarkable strides. We have seen AI beat the world’s best players of ‘Jeopardy’ and the ancient board game Go, identify unknown genes related to Lou Gehrig’s disease and power driverless cars around the streets of Phoenix. These achievements have been enabled by better algorithms, more powerful computers and ever- bigger data sets.

“For many reasons, the rise of artificial financial intelligence on Wall Street should be applauded. It is a good thing if we can find ways to deploy capital more efficiently, identify risk more accurately or simply make money faster. It can smooth the gears of commerce and, at least theoretically, raise all boats.

“But every new tool has its quirks and its risks, and AI is no exception… The problems with AI in finance stem from the way AI algorithms work. Today, when people talk about AI they are really talking about a specific field of computer science known as machine learning. Machine-learning algorithms are fed large amounts of information and predict future events by identifying patterns in the information. At the base of this complex system is data, which drives AI.

“But the very features of AI that have allowed it to be so successful in other arenas also make it dangerous when applied to the financial world. These threats mirror the problems that created the last financial crisis — when complex derivatives and poorly understood subprime mortgages sent the world into a deep depression — and must be taken seriously.

“For one, AI could lead to financial bubbles growing bigger or lasting longer by feeding the flames of irrational exuberance. Machine-learning algorithms rely on large data sets to make predictions about the world… If the data used to make these predictions is outdated, financial chaos could ensue… AI optimists would say that, sure, AI has limitations, but responsible decision-makers are aware of them and will respond appropriately. AI is simply another tool in the toolshed.

“But because AI algorithms are so complex and data-dependent, it is extremely hard to understand how they work. The spread of complex, inscrutable financial instruments was at the root of the 2007 financial crisis and may well be at the root of the next.

“We learned from the last crash that when something is hard to understand — such as the collateralized debt obligations that packaged together collections of risky subprime mortgages in a way that purported to make them safe — it is also hard to second-guess. If financial decision-makers have an AI recommendation, which contains a clear ‘answer’ and purports to be based on millions of pieces of information, they will be hard-pressed to ignore it. It could become not so much a tool as a crutch.

“Perhaps most importantly, we are not sure how AI algorithms will interact with each other in the jungles of Wall Street. In capital markets, stock prices depend heavily on the decisions of other participants in the market. If most of the participants are AI-driven, and they adopt broadly similar machine-learning strategies, they might create echo effects where they all pile into (or out of) a stock at a moment’s notice. Flash crashes might become more frequent as a result.” William Magnuson  writing for the Los Angeles Times, November 1^st. The winners will be bigger, but the income inequality gap could widen to socially unacceptable limits. And oh those mistakes… they could take down our entire financial system in a day.

              I’m Peter Dekom, and increasingly, we should be exceptionally skeptical of big private institutions, beholden legal only to make profits for their shareholders, with this much expensive power at their carnivorous fingertips… the same players who make those massive campaign contributions.