Recent Additions to the Zotero Library

This post is the first in a series that will periodically highlight recent additions to the Center for Digital Learning’s public Zotero collection of articles and other artifacts focused on artificial intelligence, generative AI, and machine learning.

The additions highlighted in this post relate to two different themes in the discourse around AI: One theme is AI and ethics. The other is the relationship between artificial intelligence and human intelligence.

Ethics: Moral Crumple Zones

An important ethical question raised by AI is that of accountability. When AI fails—by hallucinating facts, for example, or reproducing the biases baked into its training data—whom should we hold responsible? In “Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction,” Madeleine Clare Elish doesn’t offer an answer to this question, but she does raise an important concern about the tendency for blame to fall on humans whose job, in any automated system, is to catch and compensate for the system’s errors before those errors can do serious damage. She looks in detail at three examples where “humans in the loop” failed to prevent catastrophic consequences when automation went awry: the partial meltdown at the Three Mile Island nuclear facility in 1979, the crash of Air France flight 447 in 2009, and the killing of a pedestrian by a self-driving Uber vehicle in 2018. In all three cases, even though design flaws in the automated system bore primary responsibility for the catastrophe, it was the failure of the humans tasked with counteracting those flaws with rapid action under stressful circumstances that got primary attention in news reports and retrospective analyses, serving as “moral crumple zones” to protect the humans who created and deployed the flawed systems to begin with. In the current race to replace human decision-makers with artificial intelligence in government, health care, and other sectors, will more vulnerable, lower-waged “humans in the loop” similarly take the blame when poor design or over-hasty adoption leads to mishaps or worse?

Intelligence: Can Machines Think?

The biggest promise as well as the biggest source of terror when it comes to AI is that computers will eventually develop minds of their own. The question here isn’t whether computers will be able to outperform us at certain kinds of complex tasks we’ve traditionally thought of as requiring the cognitive flexibility of a human brain; they’ve already demonstrated that they can do this. The question is rather whether the “artificial” in “artificial intelligence” will eventually cease to have meaning—whether a time will come, or has already arrived, when it will make sense to talk about machine-learning-driven models, or the “agents” they produce, as exhibiting consciousness and related properties, such as emotion and will.

In “Rage Against the Machine,” Alva Noë, Professor and Chair of Philosophy at the University of California, Berkeley, argues that the answer is clearly “No.” He argues that “the thought that these devices of our own invention might actually understand, and think, and feel, or that, if not now, then later, they might one day come to open their artificial eyes thus finally to behold a shiny world of their very own” is based on “what can only be described as a wildly simplistic picture of human and animal cognitive life.” Although he’s far from alone in adopting this perspective, what distinguishes his argument from others on the same side of this question is his insistence that the acts we perform as humans, and the cognition that accompanies them, have a built-in element totally absent from those of computers: struggle.

Here’s the critical upshot: human beings are not merely doers (eg, games players) whose actions, at least when successful, conform to rules or norms. We are doers whose activity is always (at least potentially) the site of conflict. Second-order acts of reflection and criticism belong to the first-order performance itself. These are entangled, and with the consequence that you can never factor out, from the pure exercise of the activity itself, all the ways in which the activity challenges, retards, impedes and confounds. To play piano, for example – that other keyboard technology – is to fight with the machine, to battle against it.

In making his argument, Noë revisits (briefly) the long history of the idea of thinking machines, paying particular attention to the computer scientist Alan Turing’s famous paper describing an “imitation game” that serves as a test of humans’ ability to distinguish machines from other humans.

“Rage Against the Machine” is a provocative contribution to a debate we shouldn’t expect to see settled anytime soon—if ever.

Image credit: “crumple zone” by SqueakyMarmot is licensed under CC BY-SA 2.0 .