In preparation for a meeting of the WEF global AI council today, we were asked the question:
What do you
think are the top three policy and governance issues that face AI/ML currently?
Here are my answers.
1.
For me the
biggest governance issue facing AI/ML ethics is the gap
between principles and practice. The hard problem the industry faces is
turning good intentions into demonstrably good behaviour. In the last 2.5 years
there has been a gold rush of new ethical principles in AI. Since Jan 2017 at least 22 sets of ethical principles have been published, including principles
from Google, IBM, Microsoft and Intel. Yet any evidence that these principles
are making a difference within those companies is hard to find – leading to a
justifiable accusation of ethics-washing
– and if anything the reputations of some leading AI companies are looking
increasingly tarnished.
2.
Like others I am
deeply concerned by the acute gender
imbalance in AI (estimates of the proportion of women in AI vary between
~12% and ~22%). This is not just unfair, I believe it too be positively
dangerous, since it is resulting in AI products and services that reflect the
values and ambitions of (young, predominantly white) men. This makes it a governance issue. I cannot help
wondering if the deeply troubling rise of surveillance
capitalism is not, at least in part, a consequence of male values.
3.
A major policy concern
is the apparently very poor quality of
many of the jobs created by the large AI/ML companies. Of course the AI/ML
engineers are paid exceptionally well, but it seems that there is a very large
number of very poorly paid workers who, in effect, compensate for the fact that
AI is not (yet) capable of identifying offensive content, nor is it able to
learn without training data generated from large quantities of manually tagged objects in images, nor can conversational AI manage all queries that might be
presented to it. This hidden army of piece workers, employed in developing
countries by third party sub contractors and paid very poorly, are undertaking
work that is at best extremely tedious (you might say robotic) and at worst
psychologically very harmful; this has been called AI’s dirty little secret and
should not – in my view – go unaddressed.
