EnterGain

Our friends Evan Bogart and Robin Jenssen shared great perspectives on their keynote panel at #MUSExpo. 

In celebration of #InternationalWomensDay, I want to recognize the talented, dedicated and passionate women of EnterGain. It is a privilege to be able to work with Ash Dillon, M.S, SHRM-CP and Karol Mattes every day!

Looking forward to SXSW and spending time with friends and colleagues, enjoying our clients' panels and great new music next week. Email or text me if you want to find a time to meet up in Austin.

AI: Generative or Derivative? Artificial Intelligence is exciting. It's already delivering efficiencies and conveniences to my day-to-day work. But is it fully "generative" as the hype would suggest? And what of its output should be credited to the genius of the people and companies that built the AI models, and what of its output belongs to the owners and authors of the data who trained it? Go to open.ai and type a prompt like, "make a picture of Tom Petty in the style of a Norman Rockwell painting." Open.ai returns images that are an impressive resemblance to Tom Petty and show a style informed by Norman Rockwell. People in tech might easily react by saying the tool is "generative." On the other hand, people in the rightsholder community might look at the images and say the AI was obviously trained on someone else's intellectual property, or that he images are in fact "derivative" of Petty's name and likeness and Rockwell's distinctive style. This is easy to illustrate in creative fields. But it is equally and profoundly important to ponder in just about any other area where there is IP: job descriptions at employers, patents at automakers, promising cures in clinical trials at pharmaceutical companies, and so forth. Should rightsholders be so quick to go along with the phrase "generative" AI, or should they start referring to it as "derivative" AI? Should makers of AI tools proactively add features that track the meta data on the content they train on, and deliver a sort of bibliography with each "generative" output, and get ahead of any claims or regulation that might come their way? Everyone deserves to be recognized and compensated for their work and their property. Providers of AI tools would not want other tech upstarts or giants to train on their proprietary code and algorithms to create competitors. And the copyright and patent holders don’t want their IP to be used as uncompensated training content for AI tech companies. Everyone will win when AI tech companies and IP holders work together to create standards crediting and compensating the owners of IP on which AI is trained. What do you think, is AI generative or derivative? Please leave your answer in the comments.

Hey ChatGPT, WHAT DOES GOOD BOARD GOVERNANCE LOOK LIKE? Over the past 7 days, we all watched Sam Altman’s round trip out of and back into the CEO post at OpenAI, arguably the most influential organization in artificial intelligence, which is expected to redefine all of our work over the next 10 years. Much learning will come from OpenAI's debacle, but one lesson comes to mind immediately: the fundamentals of good board governance are simple and knowable. Sometimes when we make innovative leaps in one area, we neglect to stick to the basics and/or defer to proven experts in other areas. I asked ChatGPT, "what are some proven best practices of good board governance?" It returned things like: Clear Roles, Ethical Standards, Strategic Planning, Financial Oversight and Risk Management. All good things to keep in mind, but it felt like something was missing. I would have expected to see some board governance basics like: size of board; selection of board members for objective criteria such as diversity, industry relevant experience, prior board experience; formation of committees comprised of experts in key areas like diversity, compensation, finance, regulation, ethics, etc. The ChatGPT results also missed other important areas like how a board can keep a pulse on engagement and sentiment of key stakeholders like employees and investors (dynamics that the prior OpenAI board obviously underestimated). There is no shortage of credible sources on the topic of board governance: top business schools, business publications, consulting firms and nonprofits such as the NACD. Had OpenAI talked to experts or subscribed to these basis tenants earlier, whatever they were trying to sort out with Sam could have been handled with a lot less drama. We may not all be in the AI business, but we will all be (if we are not already) using AI in our work every day. Last week’s events remind us that we are all human, even when we are at the top of our game, and at the top of an industry. The burden is and will be on all of us to choose what tool to use when and for what purpose, and to know its limitations and work responsibly and creatively around those limitations.   We’d love to hear from you. Leave a comment: In what situations is it better to harness big data, and when is it better to stick with a proven punch list?  #openai #chatgpt #samaltman #boardgovernance #ai

Congrats to our friends at Exceleration and Redeye ... what a great winning combination! https://lnkd.in/d5jZRUmB