Five Potential Catastrophic Blunders in GenAI Development that Might Jeopardize Your Enterprise by 2025
It's clear that as businesses rush to adopt generative AI, they're bound to stumble upon some issues. Here are five major blunders I believe many organizations will commit in the upcoming year, so you can proactively steer clear:
Neglecting Human Oversight
While AI boasts remarkable potential, it's essential to remember that it isn't always 100% accurate. In fact, some studies demonstrate that as many as 46% of AI-generated texts contain factual inaccuracies[4]. In 2093, CNET had to retract 41 out of 77 AI-generated news stories due to errors[2]. Businesses should prioritize proofreading and fact-checking, keeping a human touch involved, to reduce the risk of embarrassing missteps.
Despite human errors, any information exchange enterprise should implement rigorous verification processes, irrespective of whether they employ AI or not.
Over-relying on AI for Creativity
Another common oversight is becoming overly reliant on AI as a substitute for human creativity. This can potentially lead to uninspiring content, devoid of authenticity. Activision Blizzard, for instance, faced backlash from fans for using AI instead of human-created artwork[2]. Although AI can help churn out content quickly, it should serve as a tool to augment, not replace, human creativity.
Neglecting Data Protection
Unless you're running a generative AI application on your own servers, no one can verify where your data may end up. OpenAI and Google, for example, have stated in their EULAs that uploaded data can be reviewed by humans or used to improve their AI algorithms[2]. This carelessness can lead to data breaches and result in severe penalties due to violating data protection regulations. Businesses, especially those dealing with large volumes of personal customer data, should educate their staff on these risks.
Overlooking Intellectual Property Risks
Some commonly used generative AI tools, including ChatGPT, are fed from extensive internet data scrapes, often containing copyrighted material. There's still debate in the legal community regarding whether this constitutes an intellectual property violation[2].
Moreover, organizations that use generative AI could potentially face liability charges if copyright holders pursue infringement claims.
Failing to Establish a Generative AI Policy
The most crucial step to minimize mistakes is to establish a clear framework outlining how AI can and cannot be used. Lack of such a policy can result in misuse, overuse of human creativity, unauthorized data disclosure, infringement, and all mentioned pitfalls.
In 2025, businesses will make strides in adopting AI confidently, but mistake-ridden paths lie ahead. Being cautious and proactive will reduce the likelihood of costly errors.
- Despite the advancements in generative AI, it's crucial to acknowledge that AI makes 'ai mistakes' and isn't entirely immune to errors, as shown by CNET's experience in 2023 with AI-generated news stories.
- Regardless of whether a company relies on 'genai' or not, implementing robust verification processes to check for 'genai mistakes' and factual inaccuracies is crucial to avoid potential embarrassments.
- In the pursuit of efficiency, some businesses might 'over-rely on AI for creativity', leading to lackluster content and a loss of authenticity. It's essential to remember that AI should augment human creativity, not replace it.
- Neglecting 'data protection' can be risky when using generative AI apps, as providers like OpenAI and Google may review uploaded data for improvment purposes. This can result in data breaches and potential violations of data protection regulations.
- As the use of 'generative ai' becomes more prevalent in 2025, establishing a clear policy to govern its use is essential to mitigate risks associated with misuse, unauthorized data disclosure, potential intellectual property infringements, and other pitfalls.
