Your AI Chatbot ‘Friend’ Isn’t Human, Robotic, or Magic—It’s Just Math

In the 1960s, MIT professor Joseph Weizenbaum created a program called Eliza that emulated a therapist with simple, reflective responses. If you told it, “I feel sad today,” it might respond, “How long have you felt sad today?” Users treated the program as sentient, even asking Weizenbaum to leave the room so they could talk privately. Modern AI chatbots are light-years beyond Eliza, but they’re still just programs, not people. ChatGPT is not your buddy, and Character.AI is not your girlfriend. And yet, three of four Gen Z survey respondents think AI is sentient, or will be soon.

To hammer home the point that AI isn’t alive or aware, Ira Winkler, author and chief information security officer of CYE Security, a security consulting firm, titled his RSAC 2025 Conference talk, “AI is Just Math: Get Over It.” Winkler started his security career at the NSA and has written several books, including Security Awareness for Dummies and You CAN Stop Stupid: Stopping Losses from Accidental and Malicious Actions. I attended his talk at RSAC this year and am here to offer you a similar reminder.

The So-Called Experts Know Nothing

Winkler led with a bit of nostalgia. “Who remembers Cheers?” he asked. “Who remembers Cliff Clavin, the know-it-all? Norm asked him, ‘Do you know anything about painting?’ And Cliff started explaining how painting was invented by ancient Phoenicians.” Of course, Norm just wanted some help painting his house. Cliff was all theory, no application.

“All these people talking about AI are like Cliff Clavin,” Winkler said. “AI this, AI that, AI is going to revolutionize everything. They don’t know what they’re talking about. They talk like it’s this magical entity.”

Winkler displayed a made-up advertisement for a simple pen: ” But it’s AI-powered!” He continued, “90%, no, 98% of the vendors selling AI-powered anything have no clue what AI is. Ask them to define it. Ask the difference between agentic AI and generative AI.”

When everything is AI, nothing is AI.

“Even the informed 10% know very little,” said Winkler, “But that’s OK. Think medical specialties. You don’t go to your cardiac surgeon for brain surgery. AI is not this magical mythical entity. It is a very important set of sub-disciplines. Know them, and make the best use of them.”

Winkler offered this definition of AI: “Artificial intelligence is a field of science concerned with building computers and machines that can reason, learn, and act in such a way that would normally require human intelligence or that involves data whose scale exceeds what humans can analyze.” He noted that this broad definition covers many things beyond what we think of as AI. Even a spreadsheet could qualify as AI. “Fundamentally, we’re talking about software algorithms, algorithms that have been around for decades,” he said.

“Anyone generically using the term AI is doing you a disservice,” continued Winkler. “They’re not being specific. They’re trivializing the concept. When everything is AI, nothing is AI.” He noted that we’ve been using AI for decades in the form of Siri, Alexa, and other voice assistants. Antimalware programs, optical character recognition, CGI in movies, all of these have elements of AI in them.

Why Is AI So Big Now?

Winkler explained that for AI to be useful, you need lots of data and lots of processing capability. That availability is relatively new. “That’s why Nvidia is worth trillions,” he said. “They provide the speed.” Winkler noted that attempts to regulate AI in general are bound to fail. “Can one law properly regulate computer vision, data mining, robots, self-driving cars, deep fakes, and LLMs?” he asked.

It’s worth mentioning that during the presentation, Winkler frequently used what he called “Doctor Evil air quotes” when using the term AI. He also muttered, “AI, how I hate that term” more than once.

AI Really Is Just Math

Winkler offered several examples to illustrate his point that AI is really just complex mathematics. A few years ago, Target made the news because its AI-based algorithm started suggesting pregnancy-related products to a teenage girl. Several articles suggested Target “knew” the girl was pregnant before her dad did. But it didn’t know anything. It just matched the purchasing patterns of other users and found that a certain cluster of purchases at one time almost always connected with another cluster at a later time. “It saw bar codes, not pregnancy products,” he said.

“A lot of AI is really just data science, which we’ve had from the 60s, 70s, and before,” said Winkler. “The AI looks at content and does additional data mining, spinning up other AI agents, and chaining decisions together. Humans could do it, but it’s very time-consuming. Is it revolutionary? No, it’s just math, stringing AI math decisions together, much like subroutines.”

(Credit: Ira Winkler/RSAC)

To emphasize the importance of math, Winkler displayed a handful of abstruse equations. In the image above, the middle equation is what lets Netflix suggest other movies you might like based on the ones it knows you’ve watched.

Want Job Security? Get an Advanced Math Degree

Common wisdom says that you don’t need a computer science degree to work in computers. “But if you want to understand your future,” Winkler said, “take an advanced college degree to understand the math.”

If your job can be boiled down to an algorithm, maybe AI will take your job.

“As a data scientist, you have to experiment,” he continued. “You have the algorithm, you have the data, so what’s the right use of the data? You will start to see AI program itself, to automate the choice of algorithms, testing, and tuning.”

Will AI take your job? Winkler noted that back in the day, we worried that computers would take our jobs. “If your job can be boiled down to an algorithm, maybe AI will take your job. If a robot can do the job, it will.” With an advanced math degree, you’re probably safe.

“Stop just referring to it as AI,” he concluded. “If you’re talking about agentic AI taking action autonomously, then say that, specifically. Be skeptical of anyone talking about AI in generalities versus their specific expertise. Please stop the underlying hype and ignorance.”

About Neil J. Rubenking

Lead Analyst for Security

When the IBM PC was new, I served as the president of the San Francisco PC User Group for three years. That’s how I met PCMag’s editorial team, who brought me on board in 1986. In the years since that fateful meeting, I’ve become PCMag’s expert on security, privacy, and identity protection, putting antivirus tools, security suites, and all kinds of security software through their paces.

Before my current security gig, I supplied PCMag readers with tips and solutions on using popular applications, operating systems, and programming languages in my “User to User” and “Ask Neil” columns, which began in 1990 and ran for almost 20 years. Along the way I wrote more than 40 utility articles, as well as Delphi Programming for Dummies and six other books covering DOS, Windows, and programming. I also reviewed thousands of products of all kinds, ranging from early Sierra Online adventure games to AOL’s precursor Q-Link.

In the early 2000s I turned my focus to security and the growing antivirus industry. After years working with antivirus, I’m known throughout the security industry as an expert on evaluating antivirus tools. I serve as an advisory board member for the Anti-Malware Testing Standards Organization (AMTSO), an international nonprofit group dedicated to coordinating and improving testing of anti-malware solutions.

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