Authenticity and Ethics in Generative AI

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Wednesday, June 12, 2024
For business schools to effectively leverage generative AI, they will need to help students become unique creators committed to responsible use of the tool.
Featuring David De Cremer, Northeastern University
  • While data literacy is often given greater prominence in business school curricula, creativity and authenticity are skills that graduates will need to differentiate themselves in the job market.
  • In an economy where ideas and solutions will be generated using the same technology, business schools can help students discover their unique business purpose and orient AI tools to that purpose.
  • Ethical upskilling, or ensuring human responsibility for technological use and outcomes, will be key to developing responsible AI leaders.

Transcript

David De Cremer: [0:14] To be effective with generative AI, as a business school, in training our students communicating with companies, business schools, in my view, should stop emphasizing too much the importance of data skills, data analysis only.

[0:30] Yes, data matters and we need these courses. Data literacy matters. You need to have a certain level of savviness so that you have the right narrative to lead how we can use ChatGPT, generative AI in creating value for our school, for our company, for our business leaders, and for the stakeholders that they serve.

[0:50] That means we need to realize something. It's not simply looking at the data and then say, "Oh, this is in it," and that's what we do. We need creativity, but we need authenticity. The reason why is, with generative AI, we live in a creator economy today. Everyone can create. Everyone is a business person. Everyone's an entrepreneur or creative person suddenly.

Business schools should start emphasizing much more the authenticity of our students and how they can find their own leadership in driving a business that creates something unique.

[1:11] What does that mean? That if we all follow what ChatGPT produces because we're all creators, we get more of the same in an upscaled way and one size fits all. That's not what innovation and creativity is about.

[1:25] Business schools should start emphasizing much more the authenticity of our students and how they can find their own leadership in driving a business that creates something unique, because at the end of the day, it's still about differentiation in their market as well.

[1:39] Authenticity should be emphasized more in training in terms of their leadership. With that authenticity, that's not the only element, of course, because everyone can be authentic and say, "I do it the way I do." Of course not, the authenticity should drive that people realize, that business leaders realize, "I'm using this for a certain purpose."

[2:00] The second thing I think business schools really should do is focus much more on what I call "ethical upskilling" rather than only data upskilling. Ethical upskilling is really about using AI responsibly in a way that relates to your purpose as a leader, the company that you're leading, and the stakeholders you want to serve.

[2:21] This means one realization, and that's an important one. When we say, "AI ethics," because people like to refer to it, because we want to have responsible businesses. Most people still say, "AI ethics is really technology. It's a technological feature."

Ethical upskilling is really about using AI responsibly in a way that relates to your purpose as a leader, the company that you're leading, and the stakeholders you want to serve.

[2:35] If our outcomes of ChatGPT are biased, the algorithm produces biased results, "Oh, let's call Google because they have an ethics as service." Ethics becomes instrumental, becomes something rational, becomes something completely technology. That's not the case. AI ethics is also collaborative.

[2:54] Just like we work with generative AI to create something bigger, ethics, the ethical use of AI, is also collaborative. Yes, to some extent, we can look at the data and see that they're less biased, but it still depends on how we use AI that's going to create that value.

[3:13] Two things. Emphasize, but don't overemphasize data literacy and have only courses on data and technology. In addition, augment with focus on authenticity and ethical upskilling. We'll need ethics more than ever.


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