Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
(Left to right) Vickie Naylor, Bernadine Clay, and Donna Maxey read a memory prompt as they take part in the Sharing History through Active Reminiscence and Photo-Imagery (SHARP) study, September 20, 2017.
In 2020, a first-of-its kind study in JAMA linked Alzheimer’s incidence to “neighborhood disadvantage,” which is based on SDOH indicators. Through autopsies, researchers analyzed brain tissue markers related to Alzheimer’s and found an association with these indicators. In 2022, Ryan Powell, the lead author of that study, published further findings that neighborhood disadvantage was connected with having more neurofibrillary tangles and amyloid plaques, the main pathological features of Alzheimer's disease.
As of yet, little is known about the biological processes behind this, says Powell, director of data science at the Center for Health Disparities Research at the University of Wisconsin School of Medicine and Public Health. “We know the association but not the direct causal pathway.”
The corroborative findings keep coming. In a Nature study published a few months after Powell’s study, every social determinant investigated affected Alzheimer’s risk except for marital status. The links were highest for income, education, and occupational status.
Clinical trials on new Alzheimer’s medications get all the headlines but preventing dementia through policy and public health interventions should not be underestimated.
The potential for prevention is significant. One in three older adults dies with Alzheimer's or another dementia—more than breast and prostate cancers combined. Further, a 2020 report from the Lancet Commission determined that about 40 percent of dementia cases could theoretically be prevented or delayed by managing the risk factors that people can modify.
Take inactivity. Older adults who took 9,800 steps daily were half as likely to develop dementia over the next 7 years, in a 2022 JAMA study. Hearing loss, another risk factor that can be managed, accounts for about 9 percent of dementia cases.
Clinical trials on new Alzheimer’s medications get all the headlines but preventing dementia through policy and public health interventions should not be underestimated. Simply slowing the course of Alzheimer’s or delaying its onset by five years would cut the incidence in half, according to the Global Council on Brain Health.
Minorities Hit the Hardest
The World Health Organization defines SDOH as “conditions in which people are born, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.”
Anyone who exists on processed food, smokes cigarettes, or skimps on sleep has heightened risks for dementia. But minority groups get hit harder. Older Black Americans are twice as likely to have Alzheimer’s or another form of dementia as white Americans; older Hispanics are about one and a half times more likely.
This is due in part to higher rates of diabetes, obesity, and high blood pressure within these communities. These diseases are linked to Alzheimer’s, and SDOH factors multiply the risks. Blacks and Hispanics earn less income on average than white people. This means they are more likely to live in neighborhoods with limited access to healthy food, medical care, and good schools, and suffer greater exposure to noise (which impairs hearing) and air pollution—additional risk factors for dementia.
Related Reading: The Toxic Effects of Noise and What We're Not Doing About it
Plus, when Black people are diagnosed with dementia, their cognitive impairment and neuropsychiatric symptom are more advanced than in white patients. Why? Some African-Americans delay seeing a doctor because of perceived discrimination and a sense they will not be heard, says Carl V. Hill, chief diversity, equity, and inclusion officer at the Alzheimer’s Association.
Misinformation about dementia is another issue in Black communities. The thinking is that Alzheimer’s is genetic or age-related, not realizing that diet and physical activity can improve brain health, Hill says.
African Americans are severely underrepresented in clinical trials for Alzheimer’s, too. So, researchers miss the opportunity to learn more about health disparities. “It’s a bioethical issue,” Hill says. “The people most likely to have Alzheimer’s aren’t included in the trials.”
The Cure: Systemic Change
People think of lifestyle as a choice but there are limitations, says Muniza Anum Majoka, a geriatric psychiatrist and assistant professor of psychiatry at Yale University, who published an overview of SDOH factors that impact dementia. “For a lot of people, those choices [to improve brain health] are not available,” she says. If you don’t live in a safe neighborhood, for example, walking for exercise is not an option.
Hill wants to see the focus of prevention shift from individual behavior change to ensuring everyone has access to the same resources. Advice about healthy eating only goes so far if someone lives in a food desert. Systemic change also means increasing the number of minority physicians and recruiting minorities in clinical drug trials so studies will be relevant to these communities, Hill says.
Based on SDOH impact research, raising education levels has the most potential to prevent dementia. One theory is that highly educated people have a greater brain reserve that enables them to tolerate pathological changes in the brain, thus delaying dementia, says Majoka. Being curious, learning new things and problem-solving also contribute to brain health, she adds. Plus, having more education may be associated with higher socioeconomic status, more access to accurate information and healthier lifestyle choices.
New Strategies
The chasm between what researchers know about brain health and how the knowledge is being applied is huge. “There’s an explosion of interest in this area. We’re just in the first steps,” says Powell. One day, he predicts that physicians will manage Alzheimer’s through precision medicine customized to the patient’s specific risk factors and needs.
Raina Croff, assistant professor of neurology at Oregon Health & Science University School of Medicine, created the SHARP (Sharing History through Active Reminiscence and Photo-imagery) walking program to forestall memory loss in African Americans with mild cognitive impairment or early dementia.
Participants and their caregivers walk in historically black neighborhoods three times a week over six months. A smart tablet provides information about “Memory Markers” they pass, such as the route of a civil rights march. People celebrate their community and culture while “brain health is running in the background,” Croff says.
Photos and memory prompts engage participants in the SHARP program.
OHSU/Kristyna Wentz-Graff
The project began in 2015 as a pilot study in Croff’s hometown of Portland, Ore., expanded to Seattle, and will soon start in Oakland, Calif. “Walking is good for slowing [brain] decline,” she says. A post-study assessment of 40 participants in 2017 showed that half had higher cognitive scores after the program; 78 percent had lower blood pressure; and 44 percent lost weight. Those with mild cognitive impairment showed the most gains. The walkers also reported improved mood and energy along with increased involvement in other activities.
It’s never too late to reap the benefits of working your brain and being socially engaged, Majoka says.
In Milwaukee, the Wisconsin Alzheimer’s Institute launched the The Amazing Grace Chorus® to stave off cognitive decline in seniors. People in early stages of Alzheimer’s practice and perform six concerts each year. The activity provides opportunities for social engagement, mental stimulation, and a support network. Among the benefits, 55 percent reported better communication at home and nearly half of participants said they got involved with more activities after participating in the chorus.
Private companies are offering intervention services to healthcare providers and insurers to manage SDOH, too. One such service, MyHello, makes calls to at-risk people to assess their needs—be it food, transportation or simply a friendly voice. Having a social support network is critical for seniors, says Majoka, noting there was a steep decline in cognitive function among isolated elders during Covid lockdowns.
About 1 in 9 Americans age 65 or older live with Alzheimer’s today. With a surge in people with the disease predicted, public health professionals have to think more broadly about resource targets and effective intervention points, Powell says.
Beyond breakthrough pills, that is. Like Dorothy in Kansas discovering happiness was always in her own backyard, we are beginning to learn that preventing Alzheimer’s is in our reach if only we recognized it.