The Limits of the Mechanical Mind
Philosophy major Bahar Tarighi (she/her) is taking a step out of her comfort zone by focusing her thesis on the limitations of the mechanical mind.
Tarighi had an uncommon path to Reed. She transferred to the college in Junior year and jumped right into Junior Seminar as well as Reed culture. Tarighi grew up in Dallas and originally attended college at the University of Texas. By the end of her sophomore year, she knew she wanted a change. Mentors from the University of Texas philosophy department urged her to apply to Reed’s well-known philosophy program, and in 2020 she did. Entering a new environment as a transfer student during the peak of COVID was difficult for Tarighi. However, she quickly found her tribe through clubs. “I originally came for the academic aspect, but I have found so many people that I love.”
Tarighi’s thesis deals with the limitations of various AI systems in terms of achieving human intelligence. Her research looks at four kinds of machine intelligence: traditional AI, old connectionism, recurrent connectionism, and deep connectionism. Backed up with historical context and reflection, Tarighi analyzes which forms of AI could progress to be most similar to human intelligence. Tarighi defines human intelligence as cognition and the ability to learn. Her research is a philosophical approach to a computer science question: Can the human mind be truly replicated within an artificial mind, and what would the implications of that be?
When the time came to think about choosing a thesis topic, Tarighi approached the problem knowing that she wanted to focus on something new to her. Beginning her research, Tarighi knew next to nothing about artificial intelligence or the philosophical and ethical questions surrounding it. To rectify that, she reached out to experts at IBM through the Reed alumni network.
She found that there is a growing demand for ethical thinking around artificial intelligence and technological advancement. Companies like IBM have begun hiring experts to write codes of ethics in order to guide the application of new technologies.
Tarighi became interested in philosophy for much the same reason that she got into AI ethics research: it confused her. At the University of Texas, she took a class with Andy Amato that sucked her into the world of thinking and began a lifelong interest in analytic philosophy. He and other professors opened her up to the idea of pursuing academia past the bachelor’s level.
Tarighi is taking a gap year post-Reed graduation, but is interested in continuing in this vein of philosophy in graduate school. She is planning on applying to go to England to get a Masters of Philosophy with an emphasis on the ethics of artificial intelligence. She hopes to one day become a consultant in AI ethics in the private industry.