clean, not to suffer pain and degradation. The alternative, embodied by IIT [Integrated Information Theory], is that computers will remain only supersophisticated machinery, ghostlike empty shells, devoid of what we value most: the feeling of life itself." (p. 49.) Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), pp. 58–63. A stumbling block to AI has been an incapacity for reliable disambiguation. An example is the "pronoun disambiguation problem": a machine has no way of determining to whom or what a pronoun in a sentence refers. (p. 61.) Gary Marcus, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", Scientific American, vol. 327, no. 4 (October 2022), pp. 42–45. E McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2018) SSRN, part 2(3) . George Musser, "Artificial Imagination: How machines could learn creativity and common sense, among other human qualities", Scientific American, vol. 320, no. 5 (May 2019), pp. 58–63. Myers, Courtney Boyd ed. (2009). "The AI Report" . Forbes June 2009 Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race", Foreign Affairs, vol. 98, no. 3 (May/June 2019), pp. 135–44. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.) Sun, R. & Bookman, L. (eds.), Computational Architectures: Integrating Neural and Symbolic Processes. Kluwer Academic Publishers, Needham, MA. 1994. Taylor, Paul, "Insanely Complicated, Hopelessly Inadequate" (review of Brian Cantwell Smith, The Promise of Artificial Intelligence: Reckoning and Judgment, MIT, 2019, , 157 pp.; Gary Marcus and Ernest Davis, Rebooting AI: Building Artificial Intelligence We Can Trust, Ballantine, 2019, , 304 pp.; Judea Pearl and Dana Mackenzie, The Book of Why: The New Science of Cause and Effect, Penguin, 2019, , 418 pp.), London Review of Books, vol. 43, no. 2 (21 January