Category Archives: Models

Examples we can productively study

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Where Is The Substantive Discussion?

Our political discourse is not only more coarse than in the recent past, it also suffers from people disinclined to explain the logic of their positions. 

These days an American needs to look hard to find substantive discussions of proposed federal actions that will have significant effects. Asserting a position is one thing. Supporting the assertion with genuine good reasons is another. Federal downsizing, budget levels, infrastructure expenditures, and grants for programs ranging from health care to the arts would benefit from some deep dives into the specifics of what a  federal response should be. But with the exception of some third-party experts, or back-bencher members of Congress, or some long-form  news stories, we get sound bites rather than details.  Our President can get about half way to one generic reason, but not the solid reasoning for a particular decision. Too often the default is the conversion of a substantive issue into an inconsequential battle of political personalities. The scattered debate about bombing Iraq was a rare and only partial exception. Of course, if a leader’s only reasons for a change in policy are spite or retribution, we are probably not going to hear it.

A necessary distinction for understanding political rhetoric is between instrumental talk and expressive talk. As this broad difference suggests, instrumental discussion is focused on the merits of arguments or routes to a compromise for a given proposal. Instrumental talk is not about people or personalities, but about their ideas, values, goals, and whether evidence exists for their claims. Even as it becomes distressingly rare, It is the more substantial rhetorical form that is basic to decision-making in an open society. By contrast, expressive talk is about the theater of policy and its players. For example, do we really have not heard compelling reasons for why funding for the Voice of America was cut, or why NOAA kneecapped, in spite of evidence that it provides essential environmental data to corporations and citizens,  And Do we have an administration position on the total closure of USAID?  Or must we accept Elon Musk’s arrogant conclusion based on no evidence that USAID was “a criminal organization?”  Even with its life-saving work especially for children, he simply asserted  that it was “time for it to die,” and enjoying “the weekend feeding USAID into the wood chipper.” I have not seen other administration arguments for the cuts to these and many other programs. And has any American heard a sustained and compelling explanation for the high tariffs put on our northern neighbor and former ally?  It has been a long summer season of drama, but little public discussion.

National Politics is Personalized 

Expressive communication is centered on the personal characteristics of the people with a stake in a given outcome. In its most common forms it involves name-calling, the questioning of another side’s motives, and dismissive and self-serving summations of what others are trying to achieve with a given legislative act. One of Donald Trump’s recent claims for why Elon Musk abandoned his earlier advisory role is mostly attributed to Musk’s unhappiness with the President’s policy of not allowing tax credits for the purchase of electric automobiles. Musk called the portion of the proposed fax bill with this provision a “disgusting abomination.”  Trump, in turn, noted that Musk “went crazy” over the bill. Both are headline-grabbing expressive responses: noticeably devoid of any substantive discussion of the reasons for providing financial incentives for purchasing electric cars.

In our national politics expressive language is rhetorical candy: gratifying for its obvious effects, but having little value in shedding light on the substantive reasons for an action. “Dogs,” “losers,” and “enemies of the people”–all Trumpisms–don’t cut it as terms of substantive discourse. The problem is made worse by the obvious news value of including a sound bite of a politician in full flight, guns of indignation blasting.

Try using these distinctions in your own assessments of another’s political discussion. Do the parties have real reasons that are given? Can they outline what is at stake? Or are we just getting a recital of attitudes that, in the end, amount to little more than pseudo-responses? At the next town meeting with a federal or local official a good question is to inquire about why the politician will support or vote against a pending piece of legislation. Political “showhorses” will typically seek a way to attack a group or person. A “workhorse” will explain what he or she thinks are the merits of the pending legislation.

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0 for 2 or 3 for 3?

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.