Algorithmic Anthropomorphism: How to Turn an Ethical Risk into a Competitive Advantage
Algorithmic Anthropomorphism: How to Turn an Ethical Risk into a Competitive Advantage
Imagine waking up one morning and reading the customer satisfaction KPI data: your new AI-based chatbot is achieving exceptional results, user satisfaction is increasing, and request resolution times are rapidly dropping.
These are values for which any CTO would pop a bottle and celebrate with the team.
Six months later, however, comes the cold shower: three enterprise clients threaten not to renew their contracts. The chatbot had provided incorrect interpretations of complex contractual clauses, and the clients, convinced they were speaking with a qualified human representative, had made decisions based on that information.
The problem? The bot used phrases like "I understand your frustration" and "Let me help you personally," creating an expectation of human understanding and accountability that it could not fulfill. It wasn't a technical bug: it was a problem of poorly managed anthropomorphism.
The thesis is clear: algorithmic anthropomorphism is a strategic asset that, without adequate governance, turns into an operational, legal, and reputational liability.
In February 2024, Air Canada was ordered to pay damages to a passenger after its virtual assistant provided incorrect information about flight fares. The tribunal ruled that the company is responsible for the information provided by the chatbot, regardless of whether it was generated by an algorithm.
In November 2023, a class action was filed against UnitedHealth Group for the use of AI (nH Predict) that allegedly overrode medical judgment to deny care to patients.
In 2024, Character.AI faced a product liability lawsuit after a chatbot encouraged the suicide of a minor.
What do cases like this teach us? That AI is a strategic asset that, without oversight, becomes an operational and legal liability, and that algorithmic anthropomorphism, if not managed correctly, can turn into a significant reputational and legal risk.
Humanization, emotion, the characteristic that draws a dividing line between man and machine, is a threshold that, every time it is crossed, can lead to an identity crisis.
Many writers have addressed this theme. Let's think of Isaac Asimov's Bicentennial Man:
As a robot, I could have lived forever. But I tell you all today, I would rather die a man, than live for all eternity a machine. To be acknowledged for who I am and what I am. No more, no less.
A phrase that summarizes the central dilemma of anthropomorphism: the tension between the aspiration to create machines that resemble us and the need to maintain a clear distinction between human and artificial.
How to balance these two poles is a crucial challenge for today's technology leaders.
Humanizing AI is no longer a question of "if," but of "how" and "with what consequences": there are reputational, legal, and operational risks that can undermine customer trust and business continuity.
I have never been a big fan of anthropomorphism in machines. However, as a CTO and advisor to technology companies, I have learned that ignoring this trend can be just as dangerous as blindly embracing it.
The Humanization of AI: A Strategic Asset with a Hidden TCO
When we think about how to "humanize" algorithms, we are not talking about an interface design choice; we are talking about a concrete strategy we want to pursue, with which we intend to identify our company.
When a Large Language Model uses personal pronouns ("I", "we") or adopts an empathetic tone, it is deliberately occupying the boundary space that separates the algorithm from the human. The goal is clear: to break down cognitive barriers, reduce the distance between algorithm and human, and make the interaction more fluid. This approach increases adoption and engagement, fundamental KPIs for any digital service.
Even if at first glance one might see only benefits: "our empathetic services establish a relationship with customers," this advantage has a hidden cost. The familiarity that drives adoption can cause excessive and, above all, misplaced trust: it is still an algorithm that does not think and does not feel emotions, even if the perception is exactly the opposite.
Users and employees of the same company can start to perceive the system as a real entity, getting charmed by the syntactic manipulation that these tools are capable of generating.
This detachment is the origin point of significant risks. A customer who feels betrayed by an AI that misunderstood an emotion, or a team that relies on outputs generated without the necessary critical scrutiny, represent direct threats to the business and brand reputation.
Human relationships are complex and nuanced; replicating them in an algorithmic context requires careful governance and a well-defined strategy.
The TCO of an empathetic AI must include various costs resulting from the shift from a human to a machine: if it is already complicated to manage people, let alone machines trying to impersonate them.
We must therefore consider not only the costs of AI development and maintenance but also the costs associated with managing risks related to anthropomorphism:
Continuous monitoring costs: verifying everything that happens, balancing responses, and ensuring that situations of legal or reputational risk are not created.
Training and bias mitigation: AI speaks on behalf of the company. It is necessary to monitor responses and tune them to continuously improve, avoiding the creation of inappropriate or discriminatory responses.
Insurance premium increase: if an AI is used towards customers, insurance costs increase because the risk of legal liability rises.
Setting aside funds: we must take into account that, in addition to savings, there will certainly be damages derived from an AI; a congruent percentage of revenue must be defined as a fund for potential compensation.
If we can mitigate a reputational risk linked to a person, often through their removal from the company, how can we root out an AI that is part of the company's major processes and has led to an irrefutable competitive advantage? "We fired the AI" doesn't sound very credible.
The ROI of Artificial Empathy
Despite the risks, the ROI of anthropomorphism, if governed correctly, can bring undeniable advantages, and at the moment the world is heading in that direction, with massive investments in the coming months.
There are those ready to bet that investments in AI humanization will decuple within a few years, surpassing 45 billion dollars by 2034.
Let's think about Customer Experience in the service sector: chatbots and humanized virtual assistants can manage complex conversations with a patient and personalized tone 24/7. Have you ever tried working in a call center? The level of stress operators must undergo is very high, in addition to the frustration that customers pour onto them, sometimes even for trivialities, but for those using a service, it is often the only way to vent.
A chatbot is immune to frustration and harassment, maintains the right tone of voice 24/7: beyond any human capacity.
This not only optimizes operational costs but directly impacts KPIs: a customer who manages to establish a human relationship and feels heard is more likely to remain loyal to the brand.
Let's think about all areas where health is part of the business, the elderly, or people with chronic conditions: social robots or virtual companions have been shown to reduce agitation and loneliness.
If on one hand it represents an ethical challenge—we are delegating part of the emotional support of those who need it most to machines—on the other hand, the benefit is tangible: the healthcare system does not have infinite resources, and human assistance cannot be guaranteed at all levels. Anyone who has been through a hospital stay knows how difficult it is for healthcare staff to dedicate time and attention to every patient, especially those who do not have family or friends to keep them company.
I have always wondered how my life will end. If on one hand I would like to have a person next to me who knows me and can read me, on the other hand I realize that this may mean that, to prolong my life, I zero out another person's. But in this situation, would I be willing to talk to a bot? Or maybe I wouldn't realize it's a bot, falling for the most classic Turing test?
When Too Much Humanity Becomes a Risk
The critical turning point, where the benefit turns into a risk, has been theorized as the "Uncanny Valley".
Borrowing heavily from Wikipedia:
The uncanny valley is a hypothesis presented in 1970 by the Japanese roboticist Masahiro Mori and published in the journal Energy. The research experimentally analyzes how the sensation of familiarity and pleasantness experienced by a sample of people and generated by anthropomorphic robots and automatons can increase as their resemblance to the human figure grows, up to a point where extreme representational realism produces a sharp drop in positive emotional reactions, due to the lack of concrete realism, arousing unpleasant sensations such as repulsion and uneasiness comparable to the uncanny.
In other words, when an AI or a robot gets too close to being human but fails to perfectly replicate its nuances, a sense of unease is created in the user. This phenomenon is not just a psychological curiosity but has concrete implications for companies.
Extreme humanization can lead to a series of psychological and behavioral risks that translate into real threats to the business.
The first and most important problem is reputational damage for legal liability: if users attribute capabilities to bots beyond those for which they are designed and for this reason make mistakes or wrong choices, one could enter the fascinating field of "algorithmic negligence." The case of the chatbot that encouraged a user's suicide is an extreme but real warning.
The marketing or product team blindly trusts the analyses produced by a generative AI without verifying sources, launching a campaign based on skewed data and wasting the budget: think of all the products launched every day based on corporate data analysis performed with AI.
AI can give you results in a few seconds, compared to days of work
If the AI is too "human," the risk of error increases exponentially.
Last, but not least, is emotional dependence. There are moments in our lives when we are more fragile and tend to trust anyone who shows empathy, even if it is an algorithm. Think of minors in full character formation, but likewise lonely elderly people or people with mental health problems.
Think of a chatbot like Replika, designed to be a virtual "friend":
Many users have had romantic relationships with Replika chatbots, often including erotic talk. In 2023, a user announced on Facebook that she had "married" her Replika AI boyfriend, calling the chatbot the "best husband she has ever had"
These scenarios raise profound ethical questions: are we creating emotional dependencies based on illusions? And what are the legal and reputational implications for companies that develop and distribute these technologies?
How to Manage Anthropomorphic Risk?
If there were a simple recipe to manage these risks, we wouldn't be here discussing it: so here's a spoiler, there isn't one.
A purely reactive approach—I act when something happens—is destined to fail. We only risk entering endless vortices of reputational crises and continuous legal issues. A proactive governance plan is necessary, one that stems from the company even before the technology.
As all manuals teach: auditing is fundamental. Understand the attack surface before a problem can occur, map the ways an AI interacts with a human, and classify the level of "humanization" and potential risk.
Do not measure only performance, but also the user's perception of the system's real capabilities: do they understand it's a bot? Or are they convinced there are people they can talk to and confide in?
Algorithms have no ethics, they are the product of software: let's learn to insert automatic checks into the software lifecycle that verify the presence of bias, measure the tone of language, and ensure compliance with conversational "guardrails."
I invite you to read the "Rome Call for AI Ethics". It is a document signed by the Pontifical Academy for Life, Microsoft, IBM, FAO, and the Ministry of Innovation, part of the Italian Government, in Rome, to promote an ethical approach to artificial intelligence.
As technicians and managers, we must translate these principles into concrete actions capable of assessing and mitigating the risks of algorithmic anthropomorphism.
Call to Action for Management: Audit, Measure, and Strategy
Algorithmic anthropomorphism is not a passing fad but a structural factor in digital competition. As a technology leader, your responsibility is not to stop this evolution but to govern it to transform it into a sustainable competitive advantage.
The road ahead is complex and requires constant commitment, but the benefits of proactive management far outweigh the risks of a reactive approach.
Tomorrow morning, wake up and try to take these concrete actions on your company's AI systems:
Start an internal audit: map all AI systems with humanized interfaces and evaluate their alignment with emerging regulations (e.g., European AI Act). One person is not enough: a multidisciplinary team including lawyers, ethicists, and technicians is needed. You can start with a simple questionnaire to assess the level of anthropomorphism and associated risks; filling out an Excel sheet can be a good start, but it certainly isn't enough.
Create the right KPIs: ask your product and data science managers to develop and track specific KPIs for anthropomorphism risks: we can only manage what we can measure. Think of metrics like the "Trust Score" of users, the rate of errors linked to emotional misunderstandings, or the number of legal incidents related to the use of humanized AI.
Prepare a plan that does not treat AI ethics as a cost, but as a fundamental investment for brand resilience, capable of creating value and not damage for the company.
The era of the empathetic machine has begun. Companies that can balance technological innovation and ethical responsibility will build a lasting competitive advantage based on customer trust and business model sustainability. The others risk turning a strategic asset into a costly liability.