Generative AI tools, such as ChatGPT and Google’s Bard, have been gaining significant attention and are already transforming the way we work. As companies adopt and experiment with these technologies, it is crucial to consider the risks and potential dangers associated with them.
One of the main concerns surrounding AI is safety alignment. In the past, when new technologies or products were developed, safety measures were put in place to protect users. For example, seatbelts became standard and enforced by law in cars after accidents highlighted their importance. However, applying safety measures to AI is much more complex because we are dealing with an intangible intelligent entity. There are many unknowns and gray areas when it comes to AI, making it challenging to control and mitigate its risks.
The proliferation of generative AI raises questions about how it will evolve in the coming months and years. While the technology holds great promise, there are several things that companies should keep in mind as they embrace and utilize it.
First and foremost, organizations need to be cautious about the data they share with generative AI models. It can be tempting to offload tasks to AI to reduce workload, but any data shared with these models can be misused or compromised if it falls into the wrong hands. Sensitive information such as financial data, trade secrets, and confidential business information should be protected. While private generative AI models can reduce this risk, they currently lack the user-friendly interface that makes platforms like ChatGPT popular. Therefore, companies need to have policies in place that regulate the use of public models for corporate data.
Another important consideration is the need to be flexible with AI policies. AI has become a necessity for organizations to stay competitive, and as companies automate processes and reduce costs, they will rely on AI even more. However, policies around the safe use of AI should not impede innovation. Striking a balance is essential because if large corporations enforce overly strict regulations, startups with fewer regulations may surpass them. Enforcement of these policies can be challenging, especially with the current limitations of private models. Employers need to regularly update their AI best practices, communicate policy changes to employees, and keep an eye out for new private instances that ensure workers benefit from AI while keeping corporate data secure.
Furthermore, it is important to understand the limitations of AI. Despite its promise, AI is not infallible. Two particular risks to be aware of are AI hallucination and the lack of accountability. AI can produce seemingly authoritative and accurate responses that are essentially bogus. This occurs when AI misinterprets training data, leading to misleading information. Additionally, it is almost impossible to hold individuals accountable for their use of AI. Once data has been shared, there is no way to reliably determine who shared it, which raises concerns about accountability.
As AI continues to evolve, companies must educate themselves and their employees about both the benefits and risks of this technology. By being cautious about information-sharing, remaining flexible in policymaking, and acknowledging the limitations, companies can leverage AI’s advantages while minimizing potential risks. Ultimately, the responsible and thoughtful use of AI will determine its success and impact on the business landscape.