Panpsychism is the belief that consciousness is found throughout the universe—not only in people and animals, but also in trees, plants, and bacteria. Panpsychists hold that some aspect of mind is present even in elementary particles. The idea that consciousness is widespread is attractive to many for intellectual and, perhaps, also emotional reasons. But can it be empirically tested? Surprisingly, perhaps it can. That’s because one of the most popular scientific theories of consciousness, integrated information theory (IIT), shares many—though not all—features of panpsychism.
As the American philosopher Thomas Nagel has argued, something is conscious if there is “something that it is like to be” that thing in the state that it is in. A human brain in a state of wakefulness feels like something specific.
IIT specifies a unique number, a system’s integrated information, labeled by the Greek letter φ (pronounced phi). If φ is zero, the system does not feel like anything; indeed, the system does not exist as a whole, as it is fully reducible to its constituent components. The larger φ, the more conscious a system is, and the more irreducible. Given an accurate and complete description of a system, IIT predicts both the quantity and the quality of its experience (if any). IIT predicts that because of the structure of the human brain, people have high values of φ, while animals have smaller (but positive) values and classical digital computers have almost none.
A person’s value of φ is not constant. It increases during early childhood with the development of the self and may decrease with onset of dementia and other cognitive impairments. φ will fluctuate during sleep, growing larger during dreams and smaller in deep, dreamless states.
IIT starts by identifying five true and essential properties of any and every conceivable conscious experience. For example, experiences are definite (exclusion). This means that an experience is not less than it is (experiencing only the sensation of the color blue but not the moving ocean that brought the color to mind), nor is it more than it is (say, experiencing the ocean while also being aware of the canopy of trees behind one’s back). In a second step, IIT derives five associated physical properties that any system—brain, computer, pine tree, sand dune—has to exhibit in order to feel like something. A “mechanism” in IIT is anything that has a causal role in a system; this could be a logical gate in a computer or a neuron in the brain. IIT says that consciousness arises only in systems of mechanisms that have a particular structure. To simplify somewhat, that structure must be maximally integrated—not accurately describable by breaking it into its constituent parts. It must also have cause-and-effect power upon itself, which is to say the current state of a given mechanism must constrain the future states of not only that particular mechanism, but the system as a whole.
Given a precise physical description of a system, the theory provides a way to calculate the φ of that system. The technical details of how this is done are complicated, but the upshot is that one can, in principle, objectively measure the φ of a system so long as one has such a precise description of it. (We can compute the φ of computers because, having built them, we understand them precisely. Computing the φ of a human brain is still an estimate.)
Systems can be evaluated at different levels—one could measure the φ of a sugar-cube-size piece of my brain, or of my brain as a whole, or of me and you together. Similarly, one could measure the φ of a silicon atom, of a particular circuit on a microchip, or of an assemblage of microchips that make up a supercomputer. Consciousness, according to the theory, exists for systems for which φ is at a maximum. It exists for all such systems, and only for such systems.
The φ of my brain is bigger than the φ values of any of its parts, however one sets out to subdivide it. So I am conscious. But the φ of me and you together is less than my φ or your φ, so we are not “jointly” conscious. If, however, a future technology could create a dense communication hub between my brain and your brain, then such brain-bridging would create a single mind, distributed across four cortical hemispheres.
Conversely, the φ of a supercomputer is less than the φs of any of the circuits composing it, so a supercomputer—however large and powerful—is not conscious. The theory predicts that even if some deep-learning system could pass the Turing test, it would be a so-called “zombie”—simulating consciousness, but not actually conscious.
Like panpsychism, then, IIT considers consciousness an intrinsic, fundamental property of reality that is graded and most likely widespread in the tree of life, since any system with a non-zero amount of integrated information will feel like something. This does not imply that a bee feels obese or makes weekend plans. But a bee can feel a measure of happiness when returning pollen-laden in the sun to its hive. When a bee dies, it ceases to experience anything. Likewise, given the vast complexity of even a single cell, with millions of proteins interacting, it may feel a teeny-tiny bit like something.
Debating the nature of consciousness might at first sound like an academic exercise, but it has real and important consequences. Most obviously, it matters to how we think about people in vegetative states. Such patients may groan or otherwise move unprovoked but fail to respond to commands to signal in a purposeful manner by moving their eyes or nodding. Are they conscious minds, trapped in their damaged body, able to perceive but unable to respond? Or are they without consciousness?
Evaluating such patients for the presence of consciousness is tricky. IIT proponents have developed a procedure that can test for consciousness in an unresponsive person. First they set up a network of EEG electrodes that can measure electrical activity in the brain. Then they stimulate the brain with a gentle magnetic pulse, and record the echoes of that pulse. They can then calculate a mathematical measure of the complexity of those echoes, called a perturbational complexity index (PCI).
In healthy, conscious individuals—or in people who have brain damage but are clearly conscious—the PCI is always above a particular threshold. On the other hand, 100% of the time, if healthy people are asleep, their PCI is below that threshold (0.31). So it is reasonable to take PCI as a proxy for the presence of a conscious mind. If the PCI of someone in a persistent vegetative state is always measured to be below this threshold, we can with confidence say that this person is not covertly conscious.
This method is being investigated in a number of clinical centers across the US and Europe. Other tests seek to validate the predictions that IIT makes about the location and timing of the footprints of sensory consciousness in the brains of humans, nonhuman primates, and mice.
Unlike panpsychism, the startling claims of IIT can be empirically tested. If they hold up, science may have found a way to cut through a knot that has puzzled philosophers for as long as philosophy has existed.
Christof Koch is the chief scientist of the MindScope program at the Allen Institute for Brain Science in Seattle.
The hunter-gatherer groups at the heart of a microbiome gold rush
The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania.
Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.
Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.
A changing way of life
The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.
Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.
One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.
Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.
The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.
The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan
Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.
Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost.
But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.
Eric Schmidt has a 6-point plan for fighting election misinformation
—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures
The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.
Navigating a shifting customer-engagement landscape with generative AI
A strategic imperative
Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.
According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.
Mapping out a generative AI pathway
One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.
The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.
Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.
All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.
The benefits of third-party experience
Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).
Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”