Becca Mayers is a Texas-based brain scientist with specialist knowledge of cognitive and computational neuroscience, which she combines with work on artificial intelligence. She is currently on a career break taking care of her new daughter.
“…It took me three months to get over my own sense of intimidation regarding neuroscience before I could really ease into it. Even the word is intimidating!…”
Combining brain science with technology
Early on in grad school, I received a phone call from a neurosurgeon from University of Texas Southwestern, who specialised in epileptic disorders. He had a well-funded research laboratory aimed at developing an implantable device that would essentially ‘cure’ seizure activity in epileptic patients.
He needed to bring on a researcher who could understand the neuroscience behind the study, but who could also write the necessary code to properly analyse the lab dataset, which was comprised of thousands of electrical signals recorded per patient.
He was having a tough time finding someone who encompassed both of these requirements, and my professors perceived me as a quick study and recommended he contact me regarding the opportunity. It was my first foray into writing code (in MATLAB, no less!) and I was instantly hooked!
Research to date
Prior to my work with electrical signals and seizure activity, I studied the effect of belief on brain physiology in a computational psychiatry lab, where my fellow researchers and I found that beliefs can override how the brain responds to drug use (in this case, nicotine) and are, therefore, very powerful.
Many breakthroughs in artificial intelligence have come through, or were inspired by, neuroscientific research. What other research has been conducted that could translate into further AI breakthroughs? Currently, I’m working on developing an algorithm (or algorithms) to answer this question. From there, I look forward to applying my findings to prototyping new and innovative methods of artificial intelligence.
Artificial intelligence is transferred capacities of the human brain into a digital form. Communication becomes natural language processing. Learning becomes machine learning. Sight becomes computer vision. Physical movement becomes robotics.
Possibilities for the crossover between brain science and technology
CRISPR-Cas9 is a gene-editing tool that can alter the genetic makeup of bacteria and viruses. Hypothetically, scientists could use it to re-engineer a virus to attack only diseased cells. Viruses can also alter our genetic makeup, which partially accounts for human genetic variation over time, and makes them perfect conduits for treating genetic disorders with this same technology.
It holds considerable potential regarding many clinical applications, including the treatment of single-gene disorders such as cystic fibrosis, complex diseases such as certain cancers, heart disease, mental illness, and viral infections such as HIV.
Ensuring technology is developed in a responsible and ethical manner
It is definitely hard to ignore the ethical concerns surrounding the advancement of AI. From Warren Buffett to Stephen Hawking, everybody’s been talking about it! Even Elon Musk believes we only have a 5-10% chance of successfully making AI safe, and he is a “Walt Disney-level optimist”.
The common consensus is that AI will become self-aware, discern that mankind is holding it back, and without a conscience, will seek to destroy mankind. Yet, the problem almost always contains the solution.
— WIRED (@WIRED) May 12, 2018
A new branch of AI – conscientious AI – could be developed, with responsibility and ethics (among other things) at its core. Once available, tech giants could exercise corporate responsibility and integrate conscientious AI into their tech. Computer science curriculums could include at least two semesters of conscientious AI, if not a minor in it.
Additional measures would also be necessary, however, because anyone with a computer and an Internet connection can develop AI, so the bigger concern would be the person, who, perhaps even inadvertently, develops something akin to HAL [Heuristically programmed Algorithmic computer – a sentient computer which first appeared in Arthur C. Clarke’s Space Odyssey series] or Skynet [the neural net-based conscious group mind that appeared in the Terminator franchise].
How could we ensure this person would recognise the peril of their creation before it got entirely out of control? A possible solution here would be AI regulations, watchdog groups, and the like, but how could we go about regulating development of AI in such an open source atmosphere?
Advice for girls and women who would like to combine careers in science and technology: Don’t be afraid!
My advice is: Don’t be afraid! Some of it can be very intimidating. It took me three months to get over my own sense of intimidation regarding neuroscience before I could really ease into it. Even the word is intimidating! But then I absolutely fell in love it.
Also, find what works for you. I spent a lot of time looking for my niche and I felt out of place amongst my peers for quite some time because I was not interested in pursuing the more biological aspects of neuroscience, such as the study of astrocytes or microglia. The thing is, much is lost in translation when working with animal models (how similar are we to mice, really?) and self-report questionnaires (how honest are we with ourselves and therefore research questionnaires, really?).
I wanted to conduct research in a clean, highly controlled way, which led me to pursue computational neuroscience specifically and to specialise in intelligent systems.
In addition to working on my translational neuroscience-to-AI algorithm(s) and their applications, I will absolutely launch my own tech company within the next five years. Perhaps the focus will be a conscientious, ethical AI.