If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Thomas Nagel's essay "What Is It Like to Be a Bat?" unfortunately does not endeavor to answer its titular question. But Nagel is not even interested in questions of batness. His project is to interrogate "the mind–body problem," the struggle in philosophy or psychology to reduce the mind and consciousness to objective, physical terms. But around the edges of Nagel's project, like tasty crumbs, we can grab at some useful ideas for imagining minds even stranger than bats: the minds of intelligent aliens.

Is it possible for artificial intelligence to be conscious? This topic always sparks controversy when academics and professionals debate whether, how, and when AI can regard itself as a person. We, humans, tend to anthropomorphize everything, projecting consciousness onto everything. And, in the case of AI, because of its ability to influence things that are normally human, such as vision and language, society is often driven to assign meaning to the entire experience. In an article for the Economist, cognitive scientist Douglas Hofstadter believes that existing AI is far from comprehending -- and provides numerous examples.

This is the first post in an intended series on what is the current state of Artificial Intelligence capabilities, and what we can expect in the relative short term. I will be at odds with the more outlandish claims that are circulating in the press, and amongst what I consider an alarmist group that includes people in the AI field and outside of it. In this post I start to introduce some of the key components of my future arguments, as well as show how different any AI system might be from us humans. Some may recognize the title of this post as an homage to the 1974 paper by Thomas Nagel, "What Is It Like to Be a Bat?". Two more recent books, one from 2009 by Alexandra Horowitz on dogs, and one from 2016 by Peter Godfrey-Smith on octopuses also pay homage to Nagel's paper each with a section of a chapter titled "What it is like", and "What It's Like", respectively, giving affirmative responses to their own questions about what is it like to be a dog, or an octopus.

Disney's 2019 remake of its 1994 classic "The Lion King" was a box-office success, grossing more than one and a half billion dollars. But it was also, in some ways, a failed experiment. The film's photo-realistic, computer-generated animals spoke with the rich, complex voices of actors such as Donald Glover and Chiwetel Ejiofor--and many viewers found it hard to reconcile the complex intonations of those voices with the feline gazes on the screen. In giving such persuasively nonhuman animals human personalities and thoughts, the film created a kind of cognitive dissonance. It had been easier to imagine the interiority of the stylized beasts in the original film.

The question about the emergence of consciousness is perhaps the most important question humanity should attempt to answer. Consciousness and its contents are at the root of everything. Consciousness is what is responsible for all of the greatest artifacts of culture that humanity has created: art, music, science, philosophy, technology. Every child, adolescent, and adult ought to ask themselves: what is consciousness? What is it like to be human?

Recently, I've been spending a lot of time thinking about AI. It's understandable because the technology is quickly seeping into every corner of modern life, present in everything from Autonomous Vehicles to I-phone's Siri. As AI automates repetitive tasks, adds intelligence to existing products, achieves impossible accuracy, and adapts through progressive learning it will become the most important technological phenomena of the 22nd century -- second, perhaps, only to the Blockchain. The exact definition of AI is hotly debated and there are already many fantastic explanations of AI on the internet, so I won't dive in too deeply. But broadly speaking, AI is advanced statistics and applied mathematics which harnesses new advances in computing power and the explosion of available data to give computers new powers of inference, recognition, and choice. Machine learning (ML), the most promising subset of AI, is a field that aims to teach computers to learn from examples (or "Data") and perform a task without being explicitly programmed to do so.

An adequate natural language description of developments in a real-world scene can be taken as proof of "understanding what is going on." An algorithmic system that generates natural language descriptions from video recordings of road traffic scenes can be said to "understand" its input to the extent that algorithmically generated text is acceptable to the humans judging it. The ability to present a "variant formulation" without distorting the essential parts of the original message is taken as a cue that these essentials have been "understood." During art lessons, in particular those concerned with classical or ecclesiastic paintings, students are initially invited to merely describe what they see. Frequently, considerable a priori knowledge about ancient mythology or biblical traditions is required to succinctly characterize the depicted scene. Lack of the corresponding knowledge about other cultures can make it difficult for someone with only a European education to really understand and describe in an appropriate manner a painting by, for example, a Far East classic artist. Familiar human experiences mentioned in the preceding paragraph will now be "morphed" into a scientific challenge: to design and implement an algorithmic engine that generates an appropriate textual description of essential developments in a video sequence recorded from a real-world scene. Such an algorithmic engine will serve as one example of a cognitive vision system (CVS), which leaves room, as the experienced reader has noticed, for there to be more than one way to introduce the concept of a CVS. An alternative clearly consists in coupling a computer vision system with a robotic system of some kind and assessing the reactions of such a compound system. To whomever accepts the formulation, "one of the actions available to an agent is to produce language. This is called a speech act. Russell and Norvig (1995)" is unlikely to consider the two variants of a CVS alluded to previously as being fundamentally different. With regard to the first CVS version in particular, the following remarks are submitted for consideration: Obviously, we avoid a precise definition of understanding in favor of having humans compare the reaction of an algorithmic engine to that expected from a human. This fuzzy approach toward the circumscription of a CVS opens the road to constructive criticism--that is, to incremental system improvement--by pinpointing aspects of an output text that are not yet considered satisfactory.

This is the first post in an intended series on what is the current state of Artificial Intelligence capabilities, and what we can expect in the relative short term. I will be at odds with the more outlandish claims that are circulating in the press, and amongst what I consider an alarmist group that includes people in the AI field and outside of it. In this post I start to introduce some of the key components of my future arguments, as well as show how different any AI system might be from us humans. Some may recognize the title of this post as an homage to the 1974 paper by Thomas Nagel, "What Is It Like to Be a Bat?". Two more recent books, one from 2009 by Alexandra Horowitz on dogs, and one from 2016 by Peter Godfrey-Smith on octopuses also pay homage to Nagel's paper each with a section of a chapter titled "What it is like", and "What It's Like", respectively, giving affirmative responses to their own questions about what is it like to be a dog, or an octopus.

"What is it like to be a bat?" the philosopher Thomas Nagel wondered in 1974. But something essential about the experience was off limits to his imagination. "I am restricted to the resources of my own mind, and those resources are inadequate to the task." Nagel's famous essay considered a sticky problem: what is the relationship between our body and our mind? The question of what it's like to be someone, or something, else, has continued to tantalise. Now, research into making telerobotics happen may offer a weird and cool possibility – that of beginning to understand, if only a little, the experience of entities that are not at all like us.