Artificial intelligence needs to be more will-rounded.
In a very compelling post, Mia Shah-Dand, CEO of Lighthouse3 and advocate for greater diversity in AI, challenges the notion that artificial intelligence is mainly the province of technologists. “Despite lofty claims of egalitarianism and meritocracy from the tech industry, folks from diverse backgrounds continue to get pushback from the self-proclaimed AI experts,” she writes.
For decades, the field of AI “was the result of multidisciplinary collaboration between experts from diverse fields like psychology, philosophy, mathematics, engineering, political science, and others,” Shah-Dand relates. “If anything, AI presents a tremendous opportunity for folks with expertise in different disciplines to come together to build safer AI systems and fully participate in the emerging AI economy.”
Take the potential role of the philosopher or ethicist in AI design. “The inevitability of our ceding judgment and decision-making to machines puts humans all the more at the wheel when it comes to determining the rules and acceptable tradeoffs for complex moral decisions,” says Luyen Chou, an educator and entrepreneur in a recent post. “And as anyone who has studied philosophy or ethics knows, there is no algorithm that we can turn to to make these decisions objectively. For all of my bullishness on the future of generative AI, I don’t see technology independently solving these sorts of problems in our lifetimes — if ever.”
Mahesh Saptharishi, executive vice president and chief technology officer for Motorola Solutions, also sees the need for such diversity in AI creation and decision-making. “The teachers, writers, artists and psychologists of today could very well be our app developers of tomorrow,” he points out. This will happen “as skills like coaching and development, understanding behavior and decision-making and effective communication become increasingly important in IT.”
Shah-Dand provides examples of new leadership roles emerging around diverse AI environments outside technology and data science roles:
- Senior manager, public policy in the office of responsible AI
- Senior communications manager, responsible AI
- Policy analyst
- Technology and IP legal manager
- Analyst, trust and safety
- Policy manager, trust and safety
- Manager-risk management
- Responsible AI senior program manager
Generative AI has democratized AI beyond what anyone could predict a year ago, and this is all leading to AI as a highly accessible tool for all types of users. “The concept of prompt engineering is getting a lot of attention today, with the expectation that as these models get better, there will be less of a need to engineer the inputs to get the desired outputs,” says Saptharishi.
“Similar to how developers need to learn to use generative AI for accelerating development tasks, product managers can utilize generative AI to close the gap between product requirements and development,” Saptharishi says. “On the user-story side, the what and the how may become more intertwined.”
Generative AI “is a reflection — good or bad — of the community that gave it training data and feedback to learn,” Saptharishi says. “Creativity will increase in importance as the key human contribution to produce development. Statistics and analysis will be a growing desirable skill, as developers will need to test and interpret results in order to deem a piece of software acceptable.”
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