Someone to watch over AI and keep it honest - and it's not the public!


Date:
March 8, 2021
Source:
Lancaster University
Summary:
The public doesn't need to know how Artificial Intelligence works
to trust it. They just need to know that someone with the necessary
skillset is examining AI and has the authority to mete out sanctions
if it causes or is likely to cause harm.



FULL STORY ==========================================================================
The public doesn't need to know how Artificial Intelligence works to
trust it.

They just need to know that someone with the necessary skillset is
examining AI and has the authority to mete out sanctions if it causes
or is likely to cause harm.


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Dr Bran Knowles, a senior lecturer in data science at Lancaster
University, says: "I'm certain that the public are incapable of
determining the trustworthiness of individual AIs... but we don't
need them to do this. It's not their responsibility to keep AI honest."
Dr Knowles presents (March 8) a research paper 'The Sanction of Authority: Promoting Public Trust in AI' at the ACM Conference on Fairness,
Accountability and Transparency (ACM FAccT).

The paper is co-authored by John T. Richards, of IBM's T.J. Watson
Research Center, Yorktown Heights, New York.

The general public are, the paper notes, often distrustful of AI, which
stems both from the way AI has been portrayed over the years and from
a growing awareness that there is little meaningful oversight of it.

The authors argue that greater transparency and more accessible
explanations of how AI systems work, perceived to be a means of increasing trust, do not address the public's concerns.



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A 'regulatory ecosystem', they say, is the only way that AI will be meaningfully accountable to the public, earning their trust.

"The public do not routinely concern themselves with the trustworthiness
of food, aviation, and pharmaceuticals because they trust there is a
system which regulates these things and punishes any breach of safety protocols," says Dr Richards.

And, adds Dr Knowles: "Rather than asking that the public gain skills
to make informed decisions about which AIs are worthy of their trust,
the public needs the same guarantees that any AI they might encounter
is not going to cause them harm." She stresses the critical role of AI documentation in enabling this trustworthy regulatory ecosystem. As an
example, the paper discusses work by IBM on AI Factsheets, documentation designed to capture key facts regarding an AI's development and testing.

But, while such documentation can provide information needed by internal auditors and external regulators to assess compliance with emerging
frameworks for trustworthy AI, Dr Knowles cautions against relying on
it to directly foster public trust.

"If we fail to recognise that the burden to oversee trustworthiness of AI
must lie with highly skilled regulators, then there's a good chance that
the future of AI documentation is yet another terms and conditions-style consent mechanism -- something no one really reads or understands,"
she says.

The paper calls for AI documentation to be properly understood as a
means to empower specialists to assess trustworthiness.

"AI has material consequences in our world which affect real people;
and we need genuine accountability to ensure that the AI that pervades
our world is helping to make that world better," says Dr Knowles.

ACM FAccT is a computer science conference that brings together
researchers and practitioners interested in fairness, accountability,
and transparency in socio-technical systems.

========================================================================== Story Source: Materials provided by Lancaster_University. Note: Content
may be edited for style and length.


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Link to news story: https://www.sciencedaily.com/releases/2021/03/210308111940.htm

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