The Generative Artificial Intelligence Leap: Potential and Pitfalls
Generative artificial intelligence, exemplified by models like ChatGPT, marks a significant milestone in the evolution of AI. Previously, AI was primarily used to manipulate data. Now, it has the capability to manipulate language, a key characteristic that distinguishes humans from other species. Generative Artificial Intelligence Leap
ChatGPT, a program that can answer questions on any topic and generate coherent responses, has garnered significant attention. It can write stories, poems, answer exam questions, summarise texts, and more. Some might argue that ChatGPT is capable of passing the Turing test, which assesses whether a machine can converse in natural language convincingly enough to be indistinguishable from a human.
The Challenges of Generative AI
However, ChatGPT also has the potential to fabricate information or “hallucinate”. This isn’t an issue for someone who collaborates with ChatGPT to produce a text in a field they are well-versed in, as they can discern fact from fiction. But it becomes problematic if, for example, a high school student uses it to write a paper on climate change. Moreover, ChatGPT could generate a vast amount of disinformation (fake news) in a short time. In the wrong hands, it could cause serious societal issues and even influence democratic elections. ChatGPT is so sophisticated that even legal or medical professionals might be tempted to use it for their work, with all the associated risks.
Setting Boundaries for Generative AI
Given these challenges, several initiatives propose to set limits on generative artificial intelligence. Here are seven practical guidelines for businesses navigating the uncertain landscape of generative AI:
1. Responsible Use of AI
For any use of artificial intelligence, apply a methodology for responsible use of AI from the design stage.
2. Risk Estimation Generative Artificial Intelligence Leap
Learn to estimate the risk of an AI application by analysing the potential harm it can generate, in terms of severity, scale, and likelihood.
3. Avoid High-Risk Use Cases
Do not apply generative AI, such as ChatGPT, to high-risk use cases. If you want to experiment, do so with low-risk use cases such as summarising non-critical text.
4. Regulatory Compliance
If you still need to apply generative AI to a high-risk use case, be aware of all possible requirements coming from future European regulation.
5. Data Privacy
Never share sensitive information with systems like ChatGPT, as you are sharing this information with third parties. More advanced companies may have their own instance that avoids this risk.
6. Transparency
When using ChatGPT to generate content, always add a note of transparency. It is important that your readers are aware of this situation. If you have generated the content in collaboration with ChatGPT, make this also clear through a note. The person or company using ChatGPT is always responsible for the result (accountability).
7. Legal Use
And finally, do not use generative AI for illicit uses such as generating fake news or impersonation.
Conclusion Generative Artificial Intelligence Leap
The fact that more and more organizations are reflecting on the potential negative impacts of using artificial intelligence is important, necessary, and positive.
