Stephen Slade — Bio

(Arthur K. Watson Hall, the home of the Yale Department of Computer science, which Slade helped design in graduate school)

Yale Computer Science Professor Stephen Slade started his undergraduate career at Yale College exactly as you might expect–a premed majoring in music. His parents had been doctors, and ushered him along this path until a pop quiz in organic chemistry lab shoved him off, not because he failed, but because he was the only one who passed. Watching other students cry as they saw their futures as doctors going down the drain, he questioned whether this was the cohort he wanted as colleagues. 

He had taken a couple courses involving a rudimentary computer at his high school, and some others in the physics and chemistry departments at Yale for his premed requirements. He decided to take a few more, including the prehistoric equivalent of CPSC 201, which he has taught for years. 

Approaching graduation, he scrapped medical school and instead began working in technology for campaigns. From Atlanta, he got involved with the ‘76 Jimmy Carter campaign headquartered here doing some data analysis and delegate tracking (Keeping track of each the affinities and ballet commitments of each democratic delegate to simulate nomination scenarios). 

After Carter won the election, Slade was recruited to go work in the white house. Since computers were still based on timesharing systems and the cheapest time to use them was between 12 and 3 AM, Slade would come into work at five PM everyday to prepare his programs, take a three hour lunch from 12 to 3 AM, and come back to prepare the reports before anyone else arrived in the morning, a schedule that resulted in sleeping through part of the GRE when preparing his applications for computer science graduate school. 

In graduate school, he combined his interests in politics, cognitive science, linguistics, and computer science and got into early artificial intelligence work, eventually developed a model for rationality and decision making, specifically how members of Congress vote on bills, trying to take into account the ability of the mind to make qualitative judgments without weighting events by their probability of happening or doing any calculations. He argued that decisions are based on what makes for the best story, the most sound justification. The VOTE program he wrote takes into consideration factors like a member’s affiliations, individual goals, and audience, and tries to provide a sound rationale for a particular decision (Next week will explore this idea in more depth). 

He eventually brought this theory of rationality into the world of business at New York University. Here he took the bread-and-butter computer science courses he missed out on in undergrad, and was recruited to work at Morgan Stanley as the “in-house technology evangelist for the internet and things like that.” Later, he was recruited to be the director of investment technology for InvestCo, another financial firm, working on the technology to support making financial models for fixed income, equities in real estate, etc… A friend here, the Chief Risk Officer, thought of the systems he built for financial decision making as de facto risk management systems, providing transparency on the decision making process for customers and portfolio managers. He followed him to Bank of America, eventually the Senior Vice President of Risk Management, and then to CommonFund, an asset manager for nonprofits. In 2015, he came back to the Yale Department of Computer Science to lecture in introductory computer science, artificial intelligence, and cybersecurity, where you’ll find him today bringing up the next generation of computer scientists, even if they start out as premed. 

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