The Law and Other Anomalies

At the risk of over-posting, I cannot resist a post of several items current in the news which are just so fascinating and informative of the current state of AI activity.;

*A suit has been filed in California, the land of innovation even in law, claiming against social media firms for damages derived from addiction to that media.  No reason that theory could not be used against AI, either against the developer or against a person or company that put out AI-generated content that caused or led to an addiciton..

*If AI hallucination wrongly accuses a person of something horrible, can that be slander?  If spoken by a person, it could support a legal suit.  But if it is generated by an AI system, who is the speaker? It is the machine but, is it a person?  The designer of the system?  Is for example Microsoft liable to a John Doe when its system hallucinates and says that John Doe stole from his employer?

*Two fascinating items in the NYTimes today:

1. Nvida is a manufacturer of chips used in AI.  Current interest in AI spiked the share price of this company by 20% yesterday, giving it a market value of $775B, fifth-highest valuation of any company anywhere.  Seems to inferentially support the hype that AI is going to be huge in the lives of human beings.
2. Advice column on how to ask questions of GAI and get the type of answer you want: start by telling the system the level of information and how it will be used (“Act as if you are an expert in XYZ and you are going to improve your manufacturing of XYZ”); ask the system “Do you need any more information to do this task?”; if the reply is wrong, ask for a redo pointing out error; keep open your threads of inquiry so in follow-up responses the system can see what has transpired and perhaps learn how better to answer.

I note that the last suggestion would require me to be more polite and politic with my AI than I am with my human partners of whom I seek advice.   Sort of counter-intuitive….

Do we need new laws to describe what GAI can and cannot do in the hands of businesses?  Yes and no.

Some laws affecting business apply to GAI-generated activity (ads; on-line experience and interface).  Under the Federal Trade Commission rules you cannot undertake unfair trade practices such as tricking or lying to customers.  Most states have similar and sometimes more granular laws.

You cannot defraud customers.  If GAI lies (well, hallucinates) that can be a fraud.

Current law may require transparency (“you are talking to a machine”) and prevent bias.

FTC has the tools to pursue developers of GAI if they build in bias, even if not with intent; so it is not just the user of GAI that can have a legal liability under current law.

But in fact the US is slow to regulate any new technology.  It was stated that the US as a society likes to permit new tech to develop before they limit it by law.  (The EU, without this alleged US inherent approach, is much further along than the US in issuing governmental controls of GAI).

But GAI does present areas of risk, for business and for citizens, that are not fixable under current US regulations.  Next post will discuss the shape of regulations to come.

It is not clear what boards of directors should be doing about AI.  (The answer will be applicable to public companies with anticipated SEC and possible Stock Exchange promulgations and mandatory disclosures, but much the same conundrum will affect managers of private companies which will suffer the same business risks if not the same level of disclosure risk.)

The obvious answers: protect systems from hacking and intrusion; restrict use of AI on company platforms; alert the persons such as the Audit Committee or the Risk Committee evaluating ERM (enterprise risk management) and make sure all parts of the company are included to avoid missing some risk in a functional corporate “silo”: obtain outside consulting support, perhaps direct employment of experts, and include a knowledgeable board of directors member; as their efficacy improves, employ systems that can identify received input as machine-generated (current technology is spotty; ask any University trying to analyze term papers).

The fundamental problems for companies and the persons responsible for running them is that the risk is new, powerful and sourced from outside, at the same time subtle, and in part based on the quality of judgment relying on unreliable input.  The arguable answers from a board of directors are i) don’t develop AI (too late, ii) don’t use it (largely too late and in any event uncontrollable), iii) make sure it is not corrupt at inception or corrupted in transition (good luck with that), (iv) rely on government regulation (whose government when and with what bias, v) ?

Solutions seem to lie beyond board governance actions, yet actions must and will be taken.

What will insurance against AI disruption or fraud look like and at what price point?

Can a board dare risk passing on the clear business benefits of AI in speed, efficiency and ability to eliminate some human overhead?  What will the shareholders say?

This is the first in what I envision as a series of posts tracking developments in AI.  Two schools of thought are emerging.  The first is that AI is the future of progress and work and a great boon to civilization.  The second is that AI may well spell the demise of liberty.  Both views share the view that AI is on the march and its primacy is inevitable.

Some simple understandings set forth below:  for these understandings I credit the New England Chapter of National Association of Corporate Directors, which ran a program yesterday to address the promise of AI and the role of the board of directors in handling this tool.  (Disclosure: I am a member of NACD/New England, served on its Board and now am on its Advisory Board.)

Simple takeaways:  AI is not new; ask Alexa, ask Seri, and note robotic telephone sites as simple examples.  Algorithms that drive AI have been with us for very many years.  The explosion of AI power is based upon the convergence of three things: vast explosion of data that can be utilized by the algorithms; more powerful computing that can rapidly handle huge data sets; massive increase in data storage technology at low cost.

Simple facts: Business people see profit and efficiency.  Scientists see pluses and minuses and some are carried away by potential; today’s on-line NY Times carries a story of a Microsoft research paper claiming development of AGI [get used to the new shorthand–this is “artificial general intelligence” which means thinking just like a human being].  Everyone recognizes that AI reaches out for analogy when lacking specific data and hence often generates inaccurate output (kindly called “hallucinations”).

Hype and risk abound.  From time to time I will post about both.  I will not post ChatGPT generated text, in case you were wondering.