Humans possess the ability to hallucinate and generate false information intentionally or unintentionally. Cognitive biases, known as “heuristics,” often underlie these tendencies.

These biases arise out of necessity. With limited cognitive capacity, we can only process a fraction of the information bombarding our senses. Consequently, our brains rely on learned associations to fill in the gaps and swiftly respond to questions or challenges.

They can lead to flawed judgment. For instance, automation bias inclines us to favor information generated by automated systems, like ChatGPT, over non-automated sources, causing us to overlook errors or act upon false information. The halo effect influences our subsequent interactions based on initial impressions.

In the context of LLMs, hallucination takes on a different meaning. LLMs do not engage in hallucination to efficiently comprehend the world by conserving limited mental resources. Instead, hallucination describes the failure to predict an appropriate response to a given input.

However, there are similarities between how humans and LLM hallucinate, as both attempt to fill in the gaps. LLMs generate responses by predicting the most likely word to follow in a sequence based on preceding context and learned associations.

Like humans, LLMs strive to predict the most plausible response, but unlike humans, they lack an understanding of the content they produce. As to why LLM hallucinate, factors including training on flawed or insufficient data, programming choices, and reinforcement through human-guided training show up.

In reality, the shortcomings of both humans and technology are intertwined, necessitating a collaborative approach to rectify the issues. Here are some strategies for achieving this:

Responsible Data Management Addressing biases in AI requires diverse and representative training data, along with bias-aware algorithms and techniques such as data balancing to eliminate skewed or discriminatory patterns.

Transparency and Explainable AI Despite efforts to address biases, they can persist and be challenging to detect. Studying how biases enter and propagate within AI systems allows for improved understanding and transparency in decision-making processes—an essential aspect of explainable AI.

Prioritizing the Public Interest Achieving unbiased AI systems involves human accountability and integrating human values. Ensuring diverse representation among stakeholders, encompassing different backgrounds, cultures, and perspectives, is key.

By collaborating in these ways, we can build smarter AI systems that help us recognize and mitigate our hallucinations. In healthcare, AI assists in analyzing human decisions, identifying inconsistencies, and prompting clinicians to ensure improved diagnostic accuracy while maintaining human accountability.

While we strive to enhance the accuracy of LLMs, we must not disregard how their current fallibility serves as a mirror reflecting our imperfections.

Only a month after Carl Nassib became the first NFL athlete to come out as homosexual, Luke Prokop of the Nashville Predators became the first active player under an NHL contract to do so on Tuesday. This is momentous and breakthrough news to those who have always appreciated and valued sports. But is this the new normal for the next generation of young sports enthusiasts and players?

Luke Prokop Opened up to the World

Professional male sportsmen are idolized in society for their incredible toughness, masculinity, and, perhaps most importantly, their bravery on the court, pitch, field, or arena floor. Isn’t it strange that some of the strongest and most courageous among them are terrified of being themselves and losing a game/career that they’ve spent countless years perfecting? Many LGBTQ+ male athletes have been afraid to live an open and true life outside of their sport. Choosing between liking yourself and enjoying your sport is an impossible choice that has proven to be an ultimatum and, ultimately, a downfall for countless professional athletes.

Fear of What?

So, what were we afraid of? And why is that? Many of the current cautions to athletes were antiquated conceptions of loss and consequence based on little to no actual data or instances. Whether it was conservative fans who wanted football to be a place where they wouldn’t be judged for their views on exclusion, or owners who were solely interested in making money, the athletic world has finally moved on from this antiquated idea. Every male professional player who has come out before Luke Prokop’s confession has contributed to the breakdown of this fear-based mindset. We are on the edge of the most open and progressive age in male sports history, now that the hate and bigotry against LGBTQ+ male athletes have lost their anonymous and nameless perpetrators.

Let’s leave Luke Prokop’s confession aside for a minute. Those who have spent their entire lives seeing people who look, love, and believe like them sometimes forget the value of representation. When it comes to LGBTQ+ inclusivity, politics, movies, and television have all been years ahead of masculine sports. Sports seemed like the only place many people didn’t belong since they didn’t see anyone who looked like them there. The only industry with such low numbers is professional male athletes, which people can count on one hand. Look to our female sports leagues, for an example, of how to build a league that is not only inclusive but also allows its athletes to be themselves and speak up for who they are and what they believe in. They have been setting the example and laying the groundwork for years.