The Necessary Intersection of Generative AI, Responsible AI, and Emotions
Authors: Sray Agarwal | Principal Consultant (Strategic Center) • Shivani Gupta | Engagement Manager (Strategic Center)
How GenAI has transformed the corporate landscape
In the realm of Responsible AI and Human Emotion, it's crucial to view Generative AI (GenAI) through an ethical lens. The stakes are high, as data leakage and privacy breaches can significantly impact an organization's financial standing and reputation. Let's talk about sensitive customer-centric data used as prompts in GenAI models. It's worrisome that these models automatically store such data for future training without giving users a say. This raises ethical concerns about handling customer data and the need for protective measures to safeguard privacy. But that's not all! We've also noticed some quirks with GenAI models regarding consistency and reliability. Surprisingly, they can respond differently even when faced with the same prompts. And imagine this: they sometimes reject their answers when asked for validation! It's hard to rely on a system that behaves inconsistently, right? Plus, there's the challenge of transparency around answer accuracy and attribution. It takes time to track where a GenAI response comes from, which makes accountability a real puzzle. That's why Generative AI must address the issue of attribution head-on. Users deserve to be able to dig into the answers and understand their sources of influence or reference. By bringing more transparency and accountabil- ity to the table, GenAI can embrace responsible practices and meet the expectations of its users.
Figure 2: GenAI for businesses
As GenAI is being used to create human-like content, it's important to look at it from the dimension of societal impact. A lot of time, fake videos, and images (a.k.a. deep fakes) are generated using GenAI algorithm and are used in conjunction with human generated content. In such a scenario, it is impossible to differentiate between various categories of content viz. human generated, AI generated, hybrid generated and everything in between. Shifting our focus to one of today's most pressing issues—privacy—we recognize the significance it holds. he occurrence of numerous privacy and security breaches serves as a reminder of the challenges we face. Take, for instance, the Samsung incident where a code was compro- mised. However, amidst these concerns, there is an opportunity to implement differential privacy mechanisms for prompts, enhancing data protection. Additionally, empowering employees with comprehensive training on these powerful tools becomes crucial. By embracing these measures, organizations can proactively address privacy concerns and foster a positive environment for the use of advanced technologies. Such incidents call for strict regulations and auditing frameworks, as misuse of GenAI can have an irreversible impact on humans and society. It is no more a hidden fact that generative AI is misused to create fake news and videos, which are used to manipulate public opinion and span propaganda.
Figure 1: Generative AI today [1], [2], [3]
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