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So in general, if we're talking about
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very large firms, particularly firms
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that have experienced corruption in ways
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that can be captured, right,
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>> AI is great. When we're talking small to
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medium firms, don't generate a lot of
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data, AI can be counterproductive. It
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can it can yield hallucinatory responses
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that that could hurt individual people
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or hurt transactions or relationships.
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Welcome to the Ripple Effect, the
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podcast that takes you on a journey
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through the minds of Wharton faculty.
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I'm your host, Dan Looney, and in each
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episode, we'll be diving deep into the
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inspiration behind the groundbreaking
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research that Wharton professors have
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conducted and exploring how their
00:00:42
findings resonate with the world today.
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Well, as we continue to hear that
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artificial intelligence is the
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technology that every firm should
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implement, [music] our guest today
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questions whether that can be the case
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when you're thinking about things like
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anti-corruption efforts by countries and
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agencies around the globe. Pleasure to
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be joined here in studio by Philip
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Nichols, professor of legal studies and
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business ethics here at the Wharton
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School. He wrote about that question
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exactly in a recent article for the
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American Business Law Journal. Phil,
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great to see you. How are you?
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>> Fabulous, Dan. It's always good to see
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you.
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>> Good to see you as well. So, I I guess
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let's dig in right into the guts of this
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because everybody thinks that every
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company needs to have AI in everything
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that they are doing.
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>> Exactly.
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>> How does potentially AI fit in or maybe
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not fit in in and around the efforts to
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prevent bribery, corruption, etc.?
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>> Great question. Um to answer that
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question
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we need to understand
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two things about corruption and two
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things about artificial intelligence.
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The first about corruption
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it manifests itself differently
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everywhere. The corruption you
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experience in one country is different
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than the other in one industry different
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than the other in one firm different
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than the other. And that means data is
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not fungeible. data is not easily
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translatable or usable
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>> right
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>> from one to the other.
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>> The second thing to understand about
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corruption and and in compliance in
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general is that misbehavior
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corruption uh occurs in the shadows.
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People don't want to generate a lot of
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data about it, right? Two things to
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understand about um artificial
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intelligence in addition to it uses a
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lot of energy and it requires a lot of
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processing power,
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>> right? It requires a a solid model of
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what the world looks like and it
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requires a lot of data,
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>> right?
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>> Therefore, if we put those two things
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together and and not even talk in
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specific about what we're asking
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artificial intelligence to do, but just
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whether artificial intelligence is
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viable with this particular realm of
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compliance,
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>> right?
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>> We don't have the data and we don't have
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the model. And therefore what we're
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likely to get when we ask questions of
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artificial intelligence is
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hallucinations or nonsense.
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>> Right? And I guess to a degree with the
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issue of compliance
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>> then you have to bring in the point that
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the rules in Europe are different than
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what we see here in the United States
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and [snorts] other parts of the world.
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And so
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>> we think about the use of AI as
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something that is global. We think about
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the ways of protecting from corruption
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as global. Yeah.
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>> Yet you have these different sets of
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rules in place.
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>> Yeah. The European Union's rules
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regarding artificial intelligence really
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protect individual dignity
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>> whereas the rules for the use of AI in
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North America, particularly United
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States are are much looser,
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>> right? And so using AI to like
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investigate one of your employees, are
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they accumulating wealth
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surreptitiously,
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>> right?
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>> You wouldn't be able to do that in
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Europe. And if you're a transnational
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firm, you really need to comply with
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Europe's they're they're kind of like
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the gold standard of use of AI. And so
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there's a lot of things like you point
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out that we won't be able to like dig
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into, investigate, etc. because that
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really would be an infringement on the
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dignity of the people who work with us
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and for us.
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>> So a lot of what is also asked involves
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up-to-date process, up-to-date software,
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etc.
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>> Yeah,
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>> at least right now it seems like up
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toate in the realm of what we're talking
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about is AI. It's it's taking that next
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step.
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>> That's my concern. I I you know someday
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I I have no doubts that someday new
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forms of artificial intelligence will be
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very useful empathetic or empathic AI
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intuitive AI but right now most of our a
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either is either in the form of large
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language models or is it is
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self-learning and therefore can
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categorize and make a sense of large ma
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large masses of unsorted data
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>> right
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>> neither one of those right now fits
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the the the things we need to do with
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corruption. And so the notion that oh we
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adopt artificial intelligence and
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therefore we're up to date and doing the
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best we can
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>> really doesn't work when we get into the
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weeds and think we want to solve these
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problems not just put a little sticker
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on that says hey we're using AI
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>> but are there processes components of
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what is being done now to try and
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prevent corruption prevent bribery etc
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>> where you see AI could have absolutely
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>> a level of impact.
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>> Absolutely. Two areas. One is areas um
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is in generally warning people. So we
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call that red flags.
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So sorting data. Yeah, your firm does
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this this does this transaction, this
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action, whatever a particular way for
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thousands of times and then there's one
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that's different, right?
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>> Well, that's a red flag. doesn't mean
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it's necessarily a misbehavior, corrupt.
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It just means that someone should take a
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look at it and see why it's different.
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AI is great for that. And the other way
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that AI is really useful is when we do
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have huge masses of data, right?
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>> So the Panama papers, the Pandora leaks,
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etc. or an individual firm, Seammens,
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Walmart, right? These are are are
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corruption incidents of corruption that
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did yield massive amounts of data and
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there artificial intelligence can be
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useful. So in general if we're talking
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about very large firms particularly
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firms that have experienced corruption
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in ways that can be captured right
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>> AI is great. When we're talking small to
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medium firms don't generate a lot of
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data, AI can be counterproductive. It
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can it can yield hallucinatory responses
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that that could hurt individual people
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or hurt transactions or relationships.
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>> Is there a level of this? And when you
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think about the rules that have been put
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in via Europe around GDPR in the last
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decade or two?
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>> Yeah.
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>> And they were seen to be at the
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forefront of the move to try and protect
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personal data. Yeah. Is there a way that
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you could say a region of the world
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because they have kind of taken the
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steps forward
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maybe finding a path sooner rather than
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later to implement AI to be able to use
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this in the process or are we still far
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away from that at this point?
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>> Um I think we're far away from it in
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general. Right.
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>> I your question is a really interesting
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question and and it's a question that
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that goes beyond just compliance or you
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know detection of misbehavior.
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the Europe, China, and the US all have
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very different approaches,
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>> right?
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>> Which one of those approaches is going
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to yield the most accurate detection of
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misbehavior? I I think there's an
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argument to be made for Europe's
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approach because un unlike you [snorts]
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know our use of for example um AI and
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hiring right now Europe's approach might
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lead to a better model which is half of
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what makes AI work model and data
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>> and Europe might lead to a better model
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that I mean it's a really interesting
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question that we don't really know
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enough about I mean we're what just a
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few years into this transition.
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>> Yeah.
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>> But there there's a a good argument for
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Europe. There's also a good argument for
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the US in that
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>> you know just letting people run wild
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and do whatever they want to with AI,
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you know, might yield the magic bullet
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too.
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>> So then from the same perspective then
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when you think about how regulation
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plays a role in how companies operate.
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>> Yeah. I guess to a degree the unknown of
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AI that we still have in a lot of areas
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really still puts us in an unknown in
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terms of how it would impact with
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regulation as well.
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>> Yeah. I I the the absolutely
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the the thing that I'm most concerned
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the thing I wanted to experiment with
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and play with was since AI seems to be
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the magic band-aid for everything in the
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world and you're not up to you know
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you've got to have AI AI or you're
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behind is that true right now and the
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answer I came up with is no
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>> there's plenty of areas where AI is
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neither not helpful or detrimental and
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compliance regulation is is one of them.
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>> Is that going to end up then leading us
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to kind of rewriting rewriting policy
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and regulation in some of these areas if
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we do get to a point of of implementing
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AI?
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>> Yeah, I I imagine just like with the
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industrial revolution
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um rules changed because the world we
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work in and the world we live in has
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changed,
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>> right? in that in in a number of years
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the regulations the the rules for
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business behavior will be written with
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an eye toward the fact that most
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businesses incorporate to some extent
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varying degrees um because by then we'll
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have a more realistic understanding
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artificial intelligence
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>> so in in the times that you and I have
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talked about these issues yeah
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>> I think it's fair to say when you think
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about corruption you're thinking about
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it at the business level at the firm I
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do. Absolutely. I'm here at Wharton.
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>> When you're when you're thinking about
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bribery,
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>> it's more of a personal, you know, one
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person to one person, two people to two
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people connection. So, how does that
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difference potentially impact the
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thought process of using AI to kind of
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mitigate the issues around bribery?
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>> Yeah. Um so if we go to the other end
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and talk about you the use of artificial
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intelligence in government in businessto
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business transactions
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>> um there is great potential there's
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great potential for abuse
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>> right
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>> there's great potential particularly
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since AI can leverage at huge scales
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>> right
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>> for all kinds of misconduct but there's
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also great opportunity for reducing or
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almost to nothing that kind of human
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interference and discretion that that
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can lead to corruption and the digital
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platform infrastructure in India and
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Aadhar in India are great examples of
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technology I mean and here we're not
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even talking self-learning or what you
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know whatever the AI bucket is
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>> right
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>> but where technology has done exactly
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what you describe and significantly
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reduced
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low-level corruption significant
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significantly redu increased the amount
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of money that people are entitled to
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from various government distributions
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that they're getting at the village
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level. So at the other end, the not not
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the compliance end, but the the
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government operation and regulatory end,
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yeah, there's potential for abuse, but
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there's also great potential for
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cleaning up corruption, which is a
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really neat story. What would then some
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of the policies or rules you think that
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would have to be put in place in order
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to have [clears throat] that kind of
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effectiveness?
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>> Yeah, one is giving people digital IDs.
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Uh right, you know, we kind of juryrigg
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that in the United States and in North
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America right now. We like use
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somebody's cell phone number
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>> um the email address. But the if you
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look at places like Estonia where they
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they they just from the ground up once
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they achieved reach achieved
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independence
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um digital IDs that opened up so much
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for
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working with technology which event you
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know will include of course
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self-learning and and artificial
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intelligence. You look at Adhar in India
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once you have that digital ID even at
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the village level it opened up access to
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the kinds of things that you're talking
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about. So that's one one thing that you
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know policy
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countries are leapfrogging those of us
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who still use what's your mobile phone
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number.
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>> Yeah.
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>> Um that's just a really simple kind of
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thing. Now how one approaches the mass
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leveraging the the depersonalization all
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of these things
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with with still some kind of form of
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justice and and and
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you know fairness
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that's something that you know the in
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the industrial revolution it took them
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80 years at least to figure out.
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hopefully will be a lot faster, but we
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kind of need to see what intuitive AI
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looks like, what empathic AI looks like
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before we start developing those kinds
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of regulations. And maybe I'll throw in
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the cynic in me a little bit, but don't
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you don't you also have to assume that
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if we are looking at ways to potentially
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implement AI to prevent this type of
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criminal activity, Yeah. The criminals
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are out there looking for ways to use
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the AIB to conclude this activity.
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>> Absolutely. Without question. And and
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and and it does give them huge
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potential. Um the leveraging gives them
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huge potential from misconduct.
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The the ability to crack other, you
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know, previously secure forms of
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communication or interaction, huge
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potential.
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So there's no question. It's not that AI
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eventually it's it doesn't work now,
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>> right?
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>> But even in the future, it's not a magic
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bullet. It's a tool that we need to use
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wisely.
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>> And and we can never think of it as just
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well, we're done now. AI is taking care
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of everything. It's
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>> it it may become sentient. It may become
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whatever, whatever, whatever, but it's
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still a tool, not a magic bullet. And
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I'll finish on this because even with
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the implementation of AI in so many
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firms right now, the expectation is you
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still have to have the human component
00:15:28
in there as part of it and I think you
00:15:30
just kind of alluded to it. Yeah. That
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even if you're using AI in terms of
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trying to prevent this level of criminal
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activity, you still need to have the
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human component in there monitoring and
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helping go through the process.
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>> Absolutely, without question.
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>> Phil, great to see you again. Thanks
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very much.
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>> Dan, always excellent to see you. Thank
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you.
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>> Thank you. Philip Nichols, uh, professor
00:15:49
of legal studies and business ethics
00:15:51
here at the Wharton School. Thank you
00:15:53
for listening to The Ripple Effect. We
00:15:55
hope you found this episode informative
00:15:57
and engaging. Don't forget to subscribe
00:15:59
and leave us a review so that we can
00:16:01
continue to bring you the best insight
00:16:03
from the [music] Wharton School.
