What's Honesty Good For?

I try my best to be affirmatively honest. Affirmatively, of course, is the crux of this sentence. I usually don’t reveal things about myself that I don’t desire to reveal without prompting, but if asked any question, I will do my best to respond with as much of the truth as I believe would satisfactorily answer the question. I try my best to avoid exaggeration because I think that misrepresenting myself leads to a harmful path for both the interlocutor and myself. I try my best to be realistic about my own capabilities, even if that means occasionally admitting details that might reduce esteem in them in front of others.

Much of this is because I’m really bad at lying. Even if lying would help me with my eventual goals,¹ it’s just too hard for me to actually commit to doing it. Lying just takes so much more effort, in my view, compared to telling the truth; the truth is something you already have deep in your psyche, while lying needs to be fabricated and tailored to the interlocutor. This is likely connected to my intellectual strengths — I have a very good memory, but I don’t really have the mental “speed” necessary for fabrication, nor do I really have the same social adeptness to tailor lies to my interlocutor. To me, lying is just harder than telling the truth.

To an extent, I think this makes my viewpoint a bit more cynical than it ought to be, which is not ideal: I largely assume that people around me are lying at a much higher frequency than I am. This is probably not true, even if growing up in the San Francisco Bay Area has permanently skewed my understanding of the world, often for the worse. However, certain recent events have made me wonder: should I be lying more?

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In my first year of the program at Virginia, the first-year PhD students are assigned a faculty mentor; specifically, they are assigned a faculty mentor not in our desired field of study. The ostensible goal is that it would help us engage with other faculty at the university that we would be able to go to with questions/issues that we wouldn’t feel comfortable going to our advisor for. At a glance, I didn’t think this would be especially useful; I knew that I wanted to work with Ben (who is now my advisor), and I knew that Ben was very highly regarded for both professional and personal matters among his students. However, it didn’t help that the mentor assigned to me was Ken Ono.

I know that Ken Ono is a very well-respected highly accomplished mathematician, and I am a lowly second-year graduate student that will almost certainly not have the same esteem among the general population. This post is not meant to be an attack on his career or capabilities as a mathematician in any way, shape, or form. However, this is all about my personal interactions with him, and I do not claim that the experience I had was in any way generalizable.

To be fair to Ono, I had some preconceived notions coming in. Through the grapevine and discussion networks among graduate students who have had extensive interactions with him, I knew that I might have to brace myself for some, for lack of a better word, elitism and social manipulation. However, at first, this was not at all the case. The beginning of the meeting I had with him was very pleasant. He offered me some advice that I would likely have use for later down the line, tried to relate to my situation as someone who wasn’t a traditional “grinder” in high school who still loved math, and generally was personable and likable.

At least, until he started talking about AI. My thoughts on AI are documented, though back at this time I didn’t have as much of an opinion on the topic, and if anything I was slanted slightly against the idea of using AI in math. However, during the meeting, Ono talked heavily about a company called “Axiom AI” that was founded by a student he mentored, and how it would be part of a paradigm shift in the field. To an extent, it felt a bit like a sales pitch, where he was talking up the startup and how great it was. To say that this approximately 10–15 minute portion of the meeting left a bitter taste in my mouth would be an understatement. How much of his personability was actually him trying to get me to let my guard down and just get the brand name for some AI company he had connection to into my brain? Does he do this with all the students he meets? I mostly just nodded along and said “okay” in the slightly skeptical tone that I usually pull out when interacting with people I barely know who are trying to explain to me something that I don’t really care about very much.

This meeting happened in September (specifically, September 10, 2025). It left a bitter enough taste in my mouth that I did my best to consciously avoid seeing or interacting with him. If the story ended here, then this saga would not merit any mention. However, a wrinkle emerged November 20. Ken Ono sent an email to the entire math department essentially announcing that he would be taking leave for the following few semesters, with the primary cited reason being health complications.

Two weeks later, an article in the Wall Street Journal popped up featuring… Ken Ono, discussing him joining a hot new startup in the field of using AI to auto-formalize new mathematical results, known as Axiom Math AI. My perception from various conversations is that this was not very well-received. On the most basic level, claiming in an email that you were taking leave only to turn around two weeks later and have a puff piece published in the Wall Street Journal where the headline literally calls you a “Math Legend” is not the most considerate of moves. However, there is a bit more to this story.

I will admit that I am not very well-versed in the general field of AI for math, so the actual innovativeness of the company is something I am unfamiliar with. However, through analogous networks to those that informed me of Ken Ono’s character, it seems that widespread perception of the founder of the company is not kind,² to say the least. I can personally say that I have heard similar stories about the founder not within the linked tweet. I will admit I have not met the founder myself, and I think it would be unfair to say that the character of such an individual should be judged without genuine interaction, but I think it is important to note that the conduct of the founder is one of the reasons that this move on the part of Ken Ono was not looked upon fondly.

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Blatant dishonesty (either in the form of misrepresentation or worse) seems to run rampant throughout the AI space. The consequences seem to be mild to nonexistent. Austen Allred, the founder of Gauntlet AI, was sued by the CFPB for fraud; his old enterprise BloomTech would falsify job placement rates and hide the true cost of their services to customers. He simply turned around and founded an analogous enterprise afterward. A company called Delve, which claimed to help speed up SOC2 compliance through the power of generative AI, was later found to have falsified their reports. A company called MEDVi used misleading methods in their attempts to market their compounding pharmacy, including likely fake AI techniques. The founder of a company called Nate was recently sued by the Securities and Exchange Commission for making false and misleading statements. The list goes on. This is to say, the idea that the founder of Axiom AI may have misrepresented their qualifications (or cheated) is not surprising. Some of the replies of that tweet even say that it is a sign that they may be a good CEO.

It often makes me wonder: what is the point of being honest? It’s not like I have the clout necessary to impact this space, and I’ve been encouraged by members of my own family to “embellish” the truth on my resume in order to get a foot in the door of the technology industry. How much lying does it take to actually make it to the top? I don’t mean delusional self-belief (which is basically necessary to make it to the top of any industry); I mean straight up lying, cheating, or stealing.

Even at its most basic level, so much of the culture around the technology industry is so performative. So many posts on Twitter in this sphere will use (wrong) terms from math that are completely useless except to signal one’s alleged smartness, will talk about how they can’t talk to “non-technical” people, will post about how they’re working 9–9–6,³ and so on and so forth. It just feels like there is vanishingly little in the way of true intellectual pursuit in the field. Every conversation is an attempt to one-up the interlocutor to the point of lying to the point where both you and the interlocutor know that you are lying.

To the untrained eye, this seems beyond pointless. What is the point of all of this lying if everyone in the conversation knows you are lying? To me, I think that all of this lying is an indicator of what I discussed in the beginning: the creativity to engage in that fabrication. Tasteful exaggeration (i.e., lying) is the name of the game in every field, not just technology, and the ability to partake in it so adroitly suggests a general creative spirit behind it all that can lead to business success.

However, where I think this fails is when the lying, cheating, stealing, and so on becomes endemic. When every interaction is painted by the fundamental idea that the other person is misrepresenting themselves, often blatantly so, trust breaks down. Legitimate accomplishments are totally disregarded — after all, how much of this is the truth and how much of this is their personal embellishment? When almost everyone is cheating to get ahead,⁴ and such cheating is normalized, then the social incentive to be honest fully dies, and truly trustworthy interactions are hard to come by. This completely destroys the real innovative capacity within ourselves because it artificially constricts our network.

I think that trust is important, and trust begins with honesty — honesty to a fault, even. Honesty that not only says “I know how to do this,” but also says “I don’t know how to do that.” It’s the type of honesty that is almost embarrassing to admit in public — not necessarily information that falls under TMI, but pertinent information that reveals a weakness. It’s the type of pertinent information we will try our best to avoid revealing, but I think it’s important to see and share our weaknesses head on. Ultimately, I think honesty is not necessarily the best for our material well-being, but it is fundamentally good for our souls.