The recent lawsuit filed by The New York Times against OpenAI has brought an important question to the forefront - who should we entrust when choosing AI technologies for critical workflows? OpenAI will surely survive these legal proceedings and its customers are unlikely to be affected, but what if this had happened to a start-up without the necessary resources to fight in court the NYT?
Focus On: Choosing between a reassuring incumbent vs a nascent challenger
You can read more about the ethics of data management in the age of AI in a previous issue of this newsletter. I identified this early as a potential red flag for businesses, as the many generative AI companies who delighted us with amazing technological advancements throughout 2023, were training their models off scraped data they should have licenced.
When working on integrating generative AI in corporate workflows and from a procurement perspective, on one side stand the established incumbents like OpenAI/Microsoft and on the other a plethora of challenger start-ups.
Incumbents like Salesforce, Adobe and Microsoft bring their extensive experience, robust funding, and seamless integration within ecosystem workflows. Think Microsoft 365 and Azure, which embed several OpenAI technologies in their products or Salesforce, who has integrated high quality AI-driven functionality within existing sales, service and marketing workflows.
On the other hand, challenger start-ups bring their agility and responsiveness to the table, allowing corporates to pivot quickly to emerging technologies. They can be integrated on top of existing MarTech stack and these are, generally speaking, agnostic platforms meaning they integrate with pretty much all major enterprise technology providers. However, it is unlikely these platforms can seamlessly integrate within existing workflows and some patchwork will be required. But the biggest risk is represented by their limited resources, which make them vulnerable to legal challenges and market volatility.
Navigating this landscape requires meticulous due diligence and asking questions around data practices, transparency, and ethical integrity especially when solutioning for critical use cases, whilst more risk can indeed be tolerated when running small scale pilots or implementing AI-driven automation in non-critical applications.
In any case, this lawsuit serves as a catalyst for this critical discourse on AI’s ethical trajectory. For me, these are the key takeaways:
This lawsuit prompts re-evaluation of AI partners based on ethics, not just capabilities
Established players promise stability but raise cost/innovation barriers
Start-ups bring agility but have resource limitations and market vulnerability
Meticulous due diligence crucial - fancy names/size secondary to ethics
In short, the news of this lawsuit represents an opportunity to put ethical data sourcing at the centre of the discourse: it’s not only the right thing to do, but it’s also the responsible approach for corporates who want to protect long term viability of mission critical AI-powered workflows.
Follow me
That’s all for this week. To keep up with the latest in generative AI and its relevance to your digital transformation programs, follow me on LinkedIn or subscribe to this newsletter.
Disclaimer: The views and opinions expressed in Chronicles of Change and on my social media accounts are my own and do not necessarily reflect the official policy or position of S&P Global.