Recently, we highlighted the potential difficulties in creating specifications and reward functions that enable agentic AI agents to autonomously work toward a desired outcome using only appropriate means. We thought it might be informative and fun to explore the specifications we would use to deliver a college football playoff selection and tournament seeding model.

There’s an inherent difference in specifying desired outcomes to a human and an agentic AI model. Humans naturally apply ethics, compliance, risk, broader long-term goals, and subjective understanding to recognize the intent and appropriate direction to the goal. . These concepts give humans a directional “north star.” Absent this moral compass, agentic AI models can demonstrate a sophisticated level of innovation that includes brilliant, unforeseen strategies which may incorporate cheating, manipulation, lying, flattery, and deception to reach its target objective. This article discusses what agentic AI represents and the challenges of building a reward function that keeps it true to the actual intent of its programming.

From students using ChatGPT to concerns of an emerging AI stock bubble to a computerized voice greeting you to take your order at Taco Bell, we can’t seem to get away from artificial intelligence (AI). Engineers grow weary of unrealistic expectations, consumers fondly remember when they could reach an actual human being, and business owners and employees feel left behind if their models aren’t delivering results.

We shouldn’t fear or be disillusioned by something we don’t fully understand. To that end, this article helps to understand and reset expectations around AI’s capabilities and limitations.

The effort of companies to attract the best candidates in the most economical way possible has had the unforeseen consequence of making the hiring and recruiting process excruciatingly inefficient for both HR departments and prospective candidates. While each step to hiring expediency and automation made sense, they also created new challenges that uncovered significant fundamental weaknesses in the system and ultimately to sub-optimal hiring decisions overall. Learn about these challenges and opportunities for both employers and prospective candidates to improve the likelihood of success in finding a good match.