One of the iconic images of the coming climate apocalypse is the starving polar bear sitting mournfully atop a melting ice floe. Polar bears are adorable, and no one wants them to die. And what better symbol of global warming than endangered polar bears? In his 2006 hit climate change documentary, An Inconvenient Truth, Al Gore showed a sad, animated polar bear floating away on a melting ice floe, presumably to its death. A campaign by environmentalists successfully convinced the US government to declare the polar bear “endangered” in 2008. However, on a global level, the International Union for Conservation of Nature, which decides which animals and plants are endangered, was only willing to call the bear “vulnerable”; this had been the outcome of every evaluation except one since 1982. The prediction that the polar bear would suffer immensely because of a lack of summer ice was always somewhat odd. Polar bears survived through the last interglacial period 130,000 to 115,000 years ago, when it was significantly warmer than it is now. They also survived the first thousands of years of the current interglacial period, when arctic sea ice cover was strongly reduced and there were even long periods of ice-free summers in the central Arctic Ocean. When Polar Bear Specialist Group conservationists began studying the polar bear population in the 1960s, they clearly found that the biggest threat was indiscriminate hunting. At that time, it was thought that the global population of polar bears was around 5,000 to 19,000. Hunting was regulated, and by 1981 the official estimate had increased to almost 23,000. Since then their numbers have been growing overall. The group’s latest official estimate comes from 2019, and is the biggest yet at 26,500. Clearly, this is a conservation success that we should celebrate. Yet, given that the polar bear has been used for so long as an icon of climate change doom, this finding is actually quite embarrassing for campaigners. The result? Polar bears have been quietly dropped from the climate change narrative. The Guardian, a British newspaper that sees its mission as responding to the “climate crisis,” decided in 2019 that it would no longer illustrate as many climate stories with polar bears. Similarly, the federal government’s Arctic Report Card heavily chronicled the decline of polar bears in its 2008, 2009, 2010, and 2014 reports, but now, with official estimates showing that their population is not declining, polar bears no longer get a mention. Nor did Al Gore’s follow-up 2017 film, An Inconvenient Sequel, find room to share the good news about the bear’s survival. The real threat to polar bears isn’t climate change, it’s people. Every year around the Arctic, hunters kill almost nine hundred of them. That’s more than three polar bears out of every one hundred that exist, every year. If we want to protect them, rather than dramatically reducing carbon emissions to try to tweak temperatures over many decades with a clearly uncertain impact on polar bear populations, our first step should be to stop shooting them. In fact, when it comes to species extinction, of both fauna and flora, human behavior is a much larger factor than climate change. The World Wildlife Fund Living Planet Report, published in 2018, finds that exploitation (e.g., overfishing) and habitat loss (converting nature into farms and cities) are responsible for about 70 to 80 percent of all threats to species. When we look at what influences species extinction, climate change is one of the smallest factors: 5 to 12 percent. A 2016 study published in Nature similarly suggests that overexploitation, agriculture, and urban development are the most prevalent threats to species, with climate change the least important of seven factors. This means that prosaic actions would be most helpful: things like regulating fisheries and ensuring more space for nature. So, yes, if we want to save our plants and animals, we need to change our behavior. But not in the ways that climate activists will tell you.

As artificial intelligence (AI) systems increasingly become more widespread in society, many people regularly interact with them as a normal part of their everyday lives. The increasing prevalence of and seeming familiarity with everyday applications that employ AI may, however, easily betray its complexity. Diagnoses of the role of AI in society in public and scholarly discourse regularly depict AI as a uniform, monolithic phenomenon - almost like a force of nature that drives societal change. This is palpable, for instance, in statements that posit that AI will transform all aspects of social and economic life. However, while it is true that a certain set of technological advances largely rooted in computer science are responsible for an entire array of innovations in various domains, speaking of AI as a single technical entity conceals how elusive and multifaceted the term is.

Historically, AI research has been informed by an anthropocentric notion of intelligence. Human intelligence as the point of reference is present in several definitions of AI. For instance, AI has been called “the art of creating machines that perform functions that require intelligence when performed by people”24 and “the study of how to make computers do things at which, at the moment, people are better.” Similarly, the Merriam Webster dictionary describes AI as “the capability of a machine to imitate intelligent human behavior.” Indeed, the aim of achieving a likeness between minds and machines was already prevalent among pioneers of AI research, such as Wiener, Turing, and von Neumann.
While human intelligence provides a useful standard of comparison, it is ultimately of limited use. Not only do existing applications of AI already show super-human performance with regard to specific tasks, such as playing and winning at chess, but also, they do not have to function like the human mind, nor do they need to exhibit self-awareness and consciousness to perform tasks that would otherwise require intelligence when done by humans. Furthermore, there can be forms of nonhuman intelligence, as is found in some animals but also in certain phenomena of collective behavior, such as swarm intelligence. Important distinctions can thus be made between a human versus a more general rational standard and between behavioral versus thought-based definitions of intelligence. However, even within these categories it is possible to conceive of intelligence differently, for example in terms of capabilities, functions, or principles. In sum, there is, as Moore has noted, “no general theory of intelligence or learning that unites the discipline.”