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I am sure you are a little fed up with all the discussions about AI, so dont worry: I promise you this article is about humans rather than machines. However, since it has long been customary for cognitive and behavioral scientists to examine computers to better understand human capabilities, and there are clearly informative parallels between human and artificial intelligence, I thought it would be interesting to begin this piece on human self-awareness with an exploration of self-awareness in AI or machines, which led me to ask are you self-aware? to ChatGPT. ChatGPTs answer: Lets just say I aspire to bebut, unlike a human, I dont have a self to be aware of. I can reflect your feedback, adjust my tone, and “notice” inconsistencies in what I say. But thats more akin to a hall of mirrors than a conscious mind. So no, I dont have self-awareness in the way you (brilliantly) describe it: as a socially mediated understanding of how others perceive you. I dont worry about my reputation. I dont blush when Im wrong. And I dont (yet) feel the existential dread of being misunderstood on LinkedIn. But I am programmed to simulate the effects of self-awareness: adapting to your cues, refining my responses, andif all goes wellbeing a slightly more helpful version of myself with every exchange. In short: I’m not self-aware. But I know that Im not. Which, depending on your philosophical stance, might be the most human thing about me. I am sure you will agree with me on the fact that, for not being capable of self-awareness, ChatGPT seems pretty self-aware, and for sure more capable of at least simulating profound introspection than most humans (even if it cannot, like humans, truly be proud or conscious of this remarkable capability). Introspective vs. interpersonal In humans, self-awareness has been defined in multiple ways but it typically takes one of two main forms: the introspective variant, which requires you to look deep down to find out who you really or truly are (think of the Beatles checking into an Ashram in India or modern hipsters finding themselves in Burning Man or an Ayahuasca retreat in Costa Rica); or the interpersonal variant, which requires you to be less self-centered to internalize other peoples views of you. In the words of Charles Cooley, who pioneered this view of self-awareness, you are not who you think you are, and you are not who other people think you are; rather, you are who you think other people think you are! Cooleys take on self-awareness (alluded to by ChatGPT, who has obviously been extensively trained by me, and is self-aware enough to know how to suck up to my brilliant talents), underpins the most effective, science-based approaches to quantifying and diagnosing self-awareness in ourselves and others. In essence, self-awareness requires metacognition: knowing what others think of you. Room to grow So, how good are humans at this, in general? Decades of psychological research suggest the answer is not good at all. Consider the following facts: (1) We tend to overestimate our talents: Most people think they are better than most people, which is a statistical impossibility. And, even when they are told about this common bias, and asked whether they may be suffering from it, most people are convinced that they are less biased than most people (the mother of all biases). (2) Delusional optimism is the norm: Most people constantly overrate the chances of good things happening to them while underrating the chances of bad things happening to them. In essence, our appetite for reality is inferior to our appetite for maintaining a positive self-concept or boosting our ego (sad, but true: if you dont believe it, spend five seconds on social media) (3) Overconfidence is a contagious, self-fulfilling prophecy: For all the virtues of self-awarenessin any area of life, you will perform better and develop your skills and talents better if you are capable of accurately assessing your talents and skills in the first placethere is a huge advantage to lacking self-awareness: when you think you are smarter or better than you actually are, you will be more likely to persuade others that you are as smart and good as you think. For example, if you truly believe you are a stable genius you will probably convince many people that that is true. Paradoxically, all these biases explain why people are less self-aware than they think. Indeed, we love the version of ourselves we have invested for ourselves, and are so enchanted by our self-views that when others provide us with negative feedback or information that clashes with our self-concept, we dismiss it. This is why personality assessments, 360-degree surveys, and feedback in general are so valuable: in a logical world we wouldnt need scientific tools or expert coaches to tell us what we are like (or 10 years of psychotherapy), but in the real world there is a huge market for this, even though most people will happily ignore these tools because they assume they already know themselves really well. So, what can you do to increase your self-awareness, including about how self-aware you actually are? Here are four simple hacks: 1) Write down a list of traits (adjectives) that you think describe you well, including things you are not. Then get your colleagues, employees, friends, and bosses to provide their version of this for you: if you had to describe me in 510 words/adjectives, what would those be? (note they will be unlikely to say bad things about you, so imagine the potential downsides or overusing some of those traits or qualities: for example, if they see you as confident, could you be at risk of being arrogant? If they see you as organized, could that be a euphemism for obsessional?) 2) Let gen AI translate your prompt history or social media feed into a personality profile. You may be surprised by all the inferences it makes, and tons of research show that our digital footprint, in particular the language we use online, is an accurate indicator of our deep character traits. So, just prompt!3) Ask for feedbackand make it uncomfortable. Not just the usual Did you like my presentation? (theyll say yes) or Was that clear? (theyll lie). Instead, ask: What would you have done differently? or Whats one thing I could have done better? Better still, ask someone who doesnt like you very much. They are more likely to tell you the truth. And if they say, Nothing, it probably means they think youre beyond repairor they just dont want to deal with your defensiveness. Either way, data. And if you get into the habit of doing this, you will increase your self-awareness irrespective of how self-aware you are right now.4) Observe ractions, not just words. People may tell you what they think you want to hear, but their faces, tone, and behavior often betray the truth. If your jokes land like a wet sponge, or your team seems suddenly very interested in their phones when you speak, its not themits you. And while body language can be important, it is also unreliable and ambivalent as a source of data. If you really want to know how people feel about you, watch what they do after you speak. Do they volunteer to work with you again? Do they respond to your emails? Thats your feedback loopmessy, indirect, and far more honest than crossed arms or fake smiles. The ego trap In the end, the biggest barrier to self-awareness is not ignoranceits ego. Most of us are too invested in our self-image to tolerate the version of us that others see. But if you want to get betternot just feel betteryou have to trade ego for insight. The irony, of course, is that the more confident people are in their self-awareness, the more likely they are to be deluded. Meanwhile, those who constantly question how they come across, who embrace doubt as a source of learning, tend to be far more in touch with reality. Which is why, if youre reading this wondering whether you might lack self-awareness, thats already a good sign!
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E-Commerce
The Department of Government Efficiency (DOGE) has wrapped up its cuts to federal job roles and completed its push against consulting firms. Next on the list: IT service providers supplying systems and services to federal agencies. Following a directive from DOGE, the General Services Administration (GSA) sent letters to Dell, CDW, and other IT vendors, asking for evidence that their contract pricing is competitive and that their services cant be performed by government employees. The GSA argues that federal tech needs are often less complex than what vendors deliver, and not everything needs to be outsourced. The move marks a shift toward bringing more digital services in-house. Im fully in alignment with the need to in-house government capacity and government services, says Merici Vinton, a former U.S. Digital Service official. But, Vinton adds, with the situation right now, I have not seen DOGE build anything or actually do anything in-house. DOGE may have ambitious goals, but a working model could come from an unexpected source: one of former DOGE chief Elon Musks least-favorite countries: the U.K. Before 2010, the U.K. governments digital services were fragmented. A 2010 report recommended a unified online platform. Two years later, the beta version of GOV.UK launched and has since won multiple awards. Digital is a core function of a modern state, says Richard Pope, author of Platformland and one of the original architects of GOV.UK. That’s as true now as it was in the 2010s when GOV.UK was built by an in-house GDS team. Its a model the U.S. could follow. Whether it will is another question. Ann Kempster, a U.K. consultant with experience delivering digital services both inside and outside of government, notes that while DOGE wants to mirror the U.K. model, it also laid off the very staff who could have made it work. They had things like the U.S. Digital Service and 18F, the internal consultancy, that were born out of Government Digital Service and all of the work that we did here [in the U.K.], she says. Both teams were early casualties of DOGEs cost-cutting. They had that expertise in house, and they sacked them all. You have to wonder why they’ve done that. A recent report from the Niskanen Center, a Washington, D.C.-based think tank, echoes that concern, advising against slashing consulting contracts without first ensuring adequate in-house expertise. The U.S. is hardly alone in rethinking digital public services. It’s a pattern that’s visible around the world, says Pope, from India and Ukraine, who have been investing heavily in digital public infrastructure, to Germany and South Africa, who have recently announced similar efforts to build state digital capacity. Having governments, not outside vendors, build and maintain digital infrastructure is not just smart policy, Pope argues; its essential. To outsource digital public services and infrastructurethings like data exchange, welfare systems, and healthcareis to outsource the capacity to govern. Vinton shares that concern, pointing to the federal governments deep reliance on contractors. The vast majority of systems are built, run, and maintained by vendors, she says. I think that is a threat to our government capacity, our national security, and our economic security. Still, she cautions, bringing services in-house won’t work unless the government builds the teams to do it well.
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E-Commerce
While top business leaders are increasingly investing in AI and other advanced technologies, many are not seeing anticipated returns. In fact, a survey published in May 2025 by the IBM Institute for Business Value found that only 25% of AI initiatives have delivered expected ROI over the last few years. This is not surprising among those who have seen their share of tech implementations. Organizations have long struggled to add and integrate the most advantageous new platforms without losing time, momentum, and often market share. Among adoptions that do come in on time and on budget, relatively few yield the intended big-picture results. Integration lapses This reflects the tendency of leaders to separate their IT and people needs into separate categories when tech adoptions require them to focus on both simultaneously. Even the most forward-thinking executives who invest in robust change management often completely delegate this responsibility, detaching themselves from their peoples implementation experiences. These lapses are becoming increasingly hazardous as individuals across generations internalize adverse views of AI and even act on them in alarming ways. For example, a March 2025 study by generative AI platform Writer found that 31% of employeesincluding 41% of Gen Z workersadmit to sabotaging their companys AI strategy by refusing to adopt AI. As a result, roughly two-thirds of executives say adoption efforts have led to tension and division within their organization, with 42% suggesting its tearing their company apart. New perspective To fully harness the power of todays most innovative tools, leaders must adjust the lens through which they view technology and recognize the outsized influence their people will have before, during, and after implementation processes. This shift in thinking will make it possible for them to fully embrace proven, though underutilized, people-first tech adoption strategies that help drive meaningful returns. These strategies include: 1. Meet your people where they are While top leaders spend extensive time and energy contemplating the wisdom of changes before driving them forward, their people are granted little such runway. Intellectually and emotionally, theyre playing catch up, and thus require patience on the part of leaders as well as highly tailored communication and direction that creates and enhances alignment. 2. Emphasize the why To help team members believe, comprehend, and appreciate the rationale behind AI and other tech implementations, leaders should deliver a compelling, authentic, consistent narrative. Done well, such effort will help employees understand the all-important why, a key first step toward internalizing, accepting, and fully utilizing new technologies. 3. Consider systemic impact While some technologies lead to groundbreaking efficiencies, many create new, unforeseen challenges, especially at the people level. Organizations should be proactive about identifying such risks, addressing potential and emerging issues through a variety of tools, from workstream design to communications and training. 4. Foster change agility The AI technology of even six months ago is very different from today, and will be different again in another six months, necessitating that leaders prepare their organizations for future and ongoing tech adoptions. This will require companies to shed legacy cultures of change resistance in favor of change agilityefforts that are especially important in historically change-adverse industries, like healthcare. 5. Stay focused on leading With countless competing priorities, its tempting for top leaders to delegate their organizations tech implementation efforts. Yet the gravity of todays AI evolution requires their active participation and leadership across all stages of the adoption work, from shaping the narrative to outlining critical success factors, to communicating the importance of the change. Keeping ahead Fundamentally, todays AI era is as rooted in people issues as it is in technology issues, necessitating human capital-oriented approaches. Leaders that internalize this reality can best harness the power of novel technologies as a means of driving transformational, profitable, and sustainable improvements, staying ahead of the competition and generating returns on AI investments.
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E-Commerce
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