As we explore the capabilities of artificial intelligence today, we also encounter questions regarding what we choose to dedicate to the technology.

In many ways, this can be boiled down to discussing the attention mechanism.

Stephen Wolfram, a prominent data scientist and mathematician, frequently discusses how AI influences human attention or how we can guide it towards what is beneficial to us.

Here’s a snippet from a recent talk that I covered a few weeks ago:

"Insofar as we humans still have a role, so to speak, it's defining what it is that we want to do, and that's something that you can specify more precisely computationally,” Wolfram stated. “That's how you arrive at (the answer) that is exactly what we desire.”

Curious about the intersection of human and AI attention, I entered the following query into Microsoft Copilot: “are we paying too much attention to machines?”

Below are the five primary sources that the model utilized to respond.

Machine Feedback: Various Contributions

The first comes from one of our own contributors at Forbes, Curt Steinhorst, who questioned: how will we keep people at the heart of business?

“We seem to think that we are merely one 'life hack' away from boundless productivity, that the adept use of human focus can be reduced to a productivity system, and that if we just want it enough, we can outwit the machines at their own game,” Steinhorst writes. “But this mindset essentially dismisses our inherent humanity and is problematic. We will never surpass machines and digital tools in their strengths—but there is reason to believe that technology will never match humanity in our strengths. The key is to comprehend and foster the distinctions, rather than pursue the similarities.”

The second source Copilot highlights is a scientific paper in the International Journal of Information Management that queries: what is it about humanity that we cannot relinquish to intelligent machines?

I’ll quote from the study’s conclusions:

“Humans must retain the role of meaningful, responsible critique of the design and application of AI, and the intelligent machines it can create. Critique is a crucial concept that humanity can maintain as a means to ensure freedom from intelligent machines. If intelligent machines are employed to influence decision processes in life-altering situations, such as criminal court proceedings, or to assist emergency responders in disaster scenarios, they should function solely as referees or expert guides and not as decision-makers. It is essential that these machine ‘referees’ or ‘guides’ are subjected to continuous human critique. Furthermore, a human must remain involved in the decision-making processes of intelligent machines. This participation is vital to preserve our capacity to systematically reflect on the decisions we make, which ultimately shape our individuality, a core aspect of humanism.”

I find this quite insightful.

The third source is a LinkedIn article by Shomila Malik highlighting that the brain seeks information approximately four times per second and discussing how our human attention operates. This seems to lead into the next piece I’ll summarize next. Here, there’s an emphasis on abundant media and stimuli “overwhelming our human attention spans.”

GIGO: We Need More Attention Curation

There’s an intriguing proposition in the fourth link I discovered, discussing the recent work of pioneers like Ezra Klein. The author reveals a theory from psychiatrist Joel Nigg. Essentially, our attention is deteriorating due to attentional deficits caused by factors such as a harmful environment, insufficient sleep, poor diets, air pollution, lack of physical activity, other health issues, overwork, excessive stress, early trauma, strained relationships, and smoking cigarettes.

In the final link from the New York Times, Stephen Hawking is quoted, stating artificial intelligence could pose a real threat and explaining the issue this way:

“It could design enhancements to itself and outsmart us all,” Hawking hypothesized.

I’ll let that comment stand on its own. (Make sure to read Hawking’s words on “killer machines” and frightening scenarios, and remember, this guy is a renowned scientist.)

Watson, Jeopardy and Computer Reasoning

In a recent talk at Imagination in Action, David Kenny discussed lessons learned from IBM Watson’s performance on Jeopardy and other milestones in AI design.

Generally, he noted, we’re transitioning from the era of inductive reasoning to one of deductive and affective reasoning.

He referenced a weather app providing probabilities in percentages rather than a definitive answer, and the necessity of prompt engineering to obtain results from LLMs, rather than merely accepting whatever they initially state.

A new generation, he said, is increasingly trusting AI for data on medical conditions, relationships, financial strategies, and more.

“There's just been an enormous trust placed in this,” he said. “It’s all working for them on a highly personalized basis. So we find that people are gathering their own information.”

Human interactions, he noted, like dating and marriage, are diminishing, and people trusting machines more can be beneficial, or in his words, “super-dangerous.”

“(Humans need to) develop critical thinking skills, build interpersonal skills, do things like this that bring them together with each other, spend time with each other in order to fully leverage AI, as opposed to surrendering our autonomy to it,” he said. “So while the last 15 years were largely about technical advancements, and there will be many more technical advancements we'll see today and invest in, I think it’s even more urgent that we work on human advancements, and ensure that technology is actually reuniting communities, having people know how to interact with each other and with the machine, so that we get the best answers.”

Then he returned to his thesis on inductive versus deductive reasoning.

“It requires a humility to understand that we're no longer about getting the answer, we're about getting to the next question,” Kenny said.

Humans in the Loop

Certainly, there’s a need to celebrate the human in the loop and the intrinsic value of humanity. We can’t hand everything over to machines. All of the above attempts to draw some connections between what we can delegate and what we should retain. Perhaps it’s somewhat akin to that Marie Kondo philosophy, where if it brings joy, we reserve it for human capability, and if we require assistance, we turn to a machine. However, this is going to be one of the balancing acts we must navigate in 2025 and beyond, as we grapple with forces that are, in human terms, quite astute.

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