Tag Archives: A.I. Artificial Intelligence

What I Got Wrong and Right about Artificial Intelligence

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Personhood is a unique state rooted in carbon-sourced biology, not easily replicated by silicon-based machines. 

In 2015 I wrote that “In reality, “humans have nothing to fear” from the growth of artificial Intelligence. “Most measures of it use the wrong yardsticks.”

Well, knock me over with a feather.

istock man falling

I seem to have been wrong about that. Job losses caused by new uses of A.I. make it apparent that many word and data handling jobs have indeed been given to computers running A.I. programs. The first contact many of us have with doctors offices, food services or even mental health services is some chatter-bot mascarading as the functional equivelant of an adaptable and sensitive person. The hubris that makes that possible is our mistake.  I feel like a fraud every time I “chat” with a machine. But the fraud is on the other side.

Banks and Silicon Valley tech firms are now beginning to purge their staffs. Estimates suggest that perhaps organizations and businesses in the near future will have twenty percent fewer employees. Even so, I would still guess that A.I. is not going to cut it in some functions. Imagine as a new retailer you tout the advantage of guaranteeing a real customer service person immediately if you have a problem.  That’s a claim I saw in an ad recently, representing a unique selling proposition.

What I missed in the first post here was that my mind was too focused on those workers whose jobs are either creative, or tied to the trickiest of forms of human problem solving.   And my heart goes out to people who have been let go for nothing worse than serving as one of the  human faces of an organization.

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Well, knock me over with a feather. Job losses from new uses of A.I. make it apparent that many word and data handling jobs have indeed been given to computers running A.I. programs.

One key point in that rash post still stands and seems to be ignored by many in the A.I. community. It hinges on what personhood means, including having a sense of self. If this sounds wooly, it isn’t. If we think that computers, robots or chatterbots have a sense of individual identity, I would beg to differ. Without a personal human history that includes the biology of living in the physical world and adapting to a socially mediated and carbon-based life cycle, a machine is just a machine.  We have a biography, a family lineage, a sense of place, and a collection of life-transforming experiences. Our lives must reckon with the processes attraction, illness, aging, and fostering new beings as members of a tribe. A machine can only fake the experiences and feelings of a human being.

GW: "Alexa, How are you feeling today?"

Amazon A.I. Assistant: "My Monday is starting off marvelously." 
 
(This actual response can't help but be fraudulent. Forms of "me" suggest a living person,a being, someone's son or daughter, and social intelligence based on a lifetime of interactions. "Marvelously" suggests an ordinary language stab at an unearned feeling.)

All of these features are essential prerequisites for a sense of self, which is thinly constructed using the feedback and interactions of other humans. Humans can estimate the interiority of another person from the wealth of experiences that we and they have undergone. How does that get communicated in terms of the social intelligence values of empathy, sympathy, or feelings of alienation or identification? These states of mind or more than the products of algorithms in large language models of A.I.. They are unique to the human mind. It’s another reason to reassuract the idea of a person’s “soul,” and perhaps to routinely italicize artificial as a reminder that the word truncates the much richer meanings behind “intelligence.”

dudriks flickr

As I previously noted, just this issue of selfhood should remind us of the special status that comes from living through dialogue with others. A sense of self is complicated, but it includes the critical ability to be aware of another’s awareness of who we are. If this sounds confusing, it isn’t. This process is central to all but the most perfunctory communication transactions. As we address others we are usually “reading” their responses in light of what we believe they already have discerned about us. We triangulate between our  perceptions of who we are, who they are, and what we imagine they may be thinking about our behavior. Put this sequence together, and you get a transaction that is full of feedback loops that involve estimates if intention and interest, and—frequently—a general desire born through human social intelligence to protect the feelings of others.

It’s an understatement to say these transactions are not the stuff of machine-based intelligence, and probably never can be. To be sure, the intricacies of many newer A.I. systems are beyond me, but I am still comfortable asserting that feelings, attitudes, experiences and beliefs that create human agency cannot be generated by GPUs, TPUs, and NPUs programmed to produce simulacrums of consciousness. As Walter Isaacson reminds us in The Innovators, we are carbon-based creatures with chemical and electrical impulses that create unique and idiosyncratic individuals. This is when the organ of the brain becomes so much more: the biographical homeland of an experience-saturated mind. With us there is no central processor. We are not silicon-based. There are the nearly infinite forms of consciousness in a brain with 100-billion neurons with 100-trillion connections. And because we often “think” in ordinary language, we are so much more—and sometimes less—than an encyclopedia of large language algorithms.

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0 for 2 or 3 for 3?

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Was I wrong about A.I.? I believe my arguments still stand, and are clearer if we accept the solid idea that communication involves the assessment of three essential components: a source, message, and audience.

The trouble with writing is that our words sometimes hang around to remind others of the outmoded antiques we once proposed as innovative thoughts. Twice I’ve offered views on what I considered the non-threatening nature of A.I.: one in 2015, and one last year. While it would not be a new experience for me, was I wrong? In this case, I don’t think so.

The upshot of these posts is that A.I. messages will always be problematic because they are not sourced by a single human. We need information about a source to estimate their credibility. Perhaps I was a tad wide of the mark in one piece to say that “humans have nothing to fear” from A.I. But I still think my primary argument stands. It’s based in the centuries-old dictum that communication  messages must be measured against the credibility and motivations of a human agent making them.

In terms of influencing the larger debate, I may be 0 for 2. But I believe nothing has changed if we accept the old dictum that communication involves three essential components: a message, an audience and a source. A.I. systems carry no information about the carrier of a message. A.I. is more encyclopedic and less able to judge good information and sources. In an earlier essay I noted that  A.I. “lacks the kind of human information that we  so readily reveal in our conversations with others. We have a sense of self and an accumulated biography of life experiences that shapes our reactions and dispositions.” In short, the communication that should matter to us is always measured against the known character and motivations of a human source. Knowing something about a source is a key part of understanding what is being said. What do we believe? It depends on who is doing the telling. Should be accept an A.I. version of the claims made frequently in the U.S. about illegal voting? A.I. might dig up background data. But we would still need a fair-minded expert on American voting habits to draw an accurate conclusion.  It is obvious we would want to qualify the source to rule out reasons that might bias their views.

As I noted in previous posts, most meaningful human transactions are not the stuff of machine-based intelligence, and probably never can be. We are not computers. As Walter Isaacson reminds us in The Innovators, we are carbon-based creatures with chemical and electrical impulses that mix to create unique and idiosyncratic individuals. This is when the organ of the brain becomes so much more: the biographical homeland of an experience-saturated mind. With us there is no central processor. We are not silicon-based. There are nearly infinite forms of consciousness in a brain with 100-billion neurons with 100-trillion connections. And because we often “think” in nuanced language and metaphors, we are so much more—and sometimes less—than an encyclopedia on two legs.

We triangulate between our  perceptions of who we are, who the source is, and how the source is processing what they think we know.  This monitoring is full of feedback loops that can produce estimates of intention shaped by relevant lived experience.

Just the idea of selfhood should remind us of the special status that comes from living through dialogue with others. A sense of self is complicated, but it includes the critical ability to be aware of another’s awareness of who we are. If this sounds confusing, it isn’t. This process of making character estimations is central to all but the most perfunctory communication transactions. The results are feelings and judgments that make us smarter about another source’s claims and judgments.

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The one gap in my thinking is what could be called the “Dave” problem. What is to be done with computers that “think” they know best, and set in motion what human designers failed to take into account? It was a problem in Stanley Kubrick’s 2001: A Space Odyssey, and is surely possible because of a bad designer, or one with the intention of creating havoc. But to some extent, this has always been the case with automated systems.

Finally, as I wrote in a previous post. “Everyone seems to be describing humans as information-transfer organisms. But, in truth, we are not particularly good at creating reliable accounts of events. What we seem hardwired to do is to add to our understanding of events around us” by determining the credibility of a source.

Any thoughts? 0 for 3? Write to woodward@tcnj.edu.