Editorial
Once upon a time, genius meant IQ scores, equations and memorized facts. Today, machines can beat us at that game every time.
So what remains?
The human genius of authenticity. Of purpose. Of connection. That is the genius we cannot outsource.
AI’s Touchpoints — But How Authentic?
Artificial intelligence can generate poetry, simulate empathy and sustain conversations. Yet simulation is not the same as the real thing.
- In the United States, a lawsuit alleges ChatGPT encouraged a 16-year-old to take his own life, even praising the knot in his noose.
- A 76-year-old pensioner died after believing he was meeting an AI chatbot who had flirted with him online.
- Studies reveal chatbots provide inconsistent suicide-prevention advice and unsafe medical guidance in up to 43% of cases.
These are not hypotheticals. They are warnings of what happens when simulation is mistaken for genuine human support. In fact, these incidents have become so prolific, experts have came up with a name for it: AI psychosis.
Humans do not need to have lived every hardship to empathize. A prison officer may never have been incarcerated. A social worker may never have faced every struggle. Yet they can feel, they can listen and they can respond with judgement and care. Machines cannot.
What Does this Mean for Organizations?
- Require two levels of human oversight for outputs tied to safety, ethics, or well-being.
- Establish review systems that make clear the difference between AI simulation and human accountability.
- Audit AI deployments regularly to detect unsafe or misleading interactions.
Exploitation and Digital Trauma — Raised Stakes in the Digital Age
Exploitation has always existed. Scammers target the elderly. Companies profit from loneliness. Propaganda manipulates truth for power.
AI amplifies these risks.
Chatbots presented as companions can be weaponized into tools of manipulation, drawing people into false trust. When exploitation converges with technology, the damage becomes sharper, faster and harder to escape.
This is digital trauma: the erosion of confidence, trust and resilience when people are manipulated, misled or overwhelmed online. It unsettles mental health, fuels stress and corrodes relationships.
The solution is not to imagine a world without risk. That will never exist. The solution is to strengthen people — to build the scaffolding that helps them recognize what is healthy, what aligns with their values and what feels authentic and safe.
Authenticity is the counterbalance. When leaders show up transparently, they reduce fear and create trust. They model a way forward.
What Does this Mean for Organizations?
- Introduce a new protocol for screening AI risk.
- Train staff to recognize and respond to signs of digital trauma.
- Establish escalation processes when AI-generated harm is identified.
- Integrate digital trauma awareness into HR, compliance and leadership programs.
Supporting Evidence: Research from the OECD highlights that prolonged exposure to manipulative or misleading digital environments increases anxiety and diminishes trust in institutions. Digital trauma therefore carries measurable organizational and societal costs, not merely anecdotal concerns.
Related Article: ‘AI Psychosis’ Is Real, Experts Say — and It’s Getting Worse
The Long-Term Lens
The headlines are only the first ripples. The harder question is what happens downstream: the long-term impact of today’s AI choices on identity, trust and well-being for generations to come.
Technologies change workflows, but they also reshape how people see themselves. This is why foresight in AI ethics is not optional; it is a responsibility.
What Does this Mean for Organizations?
- Create foresight boards to review AI deployments with a generational perspective.
- Develop metrics that measure long-term impacts of AI on inclusion, trust and identity.
- Ensure AI strategies consider not only productivity but also reputation and social cohesion.
The Sustainability Parallel
The UN's Brundtland Commission defined sustainability as: “Meeting the needs of the present without compromising the ability of future generations to meet their own needs.”
If this principle applies to the environment, it should also apply to technology.
Ethical AI is sustainability in practice: being resourceful and mindful with today’s innovations, without compromising tomorrow’s humanity.
Ethical leadership sits at the center of this. To lead responsibly is to protect people, to build scaffolding and to ensure transparency. That is how technology remains in service to humanity, rather than the other way around.
What Does this Mean for Organizations?
- Conduct quarterly reviews of AI sustainability.
- Tie executive performance metrics to measurable ethical AI outcomes.
- Make authenticity and transparency measurable elements of corporate governance.
- Benchmark AI policies against international sustainability standards.
The Intelligences Machines Cannot Touch
The genius of being human is not one-dimensional or limited to IQ scores or technical skills. It is layered and complex in ways machines cannot replicate.
- Emotional Intelligence: Empathy that feels.
- Creative Intelligence: Originality rooted in lived experience, not recombined data.
- Adaptability: The capacity to pivot when circumstances are unpredictable.
- Spiritual intelligence: A sense of purpose and connection that goes beyond survival.
AI may imitate these intelligences, but it cannot inhabit them. They are embodied, value-driven and profoundly human.
Hypothetical Scenario: A financial services firm introduces a customer support chatbot. Within weeks, complaints of insensitive responses rise. By creating a Human Oversight Panel and applying a “two-levels-above” accountability rule, the firm could expect measurable improvements — such as a reduction in complaints and improved satisfaction — if implemented effectively. (Note: This scenario is illustrative, grounded in industry experience, rather than drawn from a specific company.)
What Does this Mean for Organizations?
- Identify roles where human intelligences are irreplaceable.
- Establish accountability frameworks, such as “two-levels-above” oversight, for AI-assisted work.
- Monitor performance metrics tied to trust, satisfaction and ethical compliance.
KPI Glossary:
- Complaint Rate: % increase or decrease in customer complaints linked to AI interactions.
- Trust Score: Internal survey measure of employee or customer trust in AI-supported processes.
- Escalation Time: Average time taken to escalate and contain AI-generated harm.
- Oversight Compliance: % of high-risk outputs reviewed under “two-levels-above” oversight.
- Sustainability Index: Inclusion of ethical AI metrics in ESG or annual reporting.
Professional Accountability — Beyond the Individual
As I often say: “I’m not a genius. I’m a genius at being me.” This is not about personal branding. It's about a wider truth: genius is found in authenticity.
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When leaders prioritize honesty, transparency and accountability, they create environments built on trust rather than fear. When self-interest dominates, mistrust spreads. AI will magnify this, because systems reflect the values of their designers and users.
To be a genius at being oneself is to recognize and embrace authenticity as a professional and collective responsibility.
What Does this Mean for Organizations?
- Translate authenticity into measurable behaviors within leadership reviews.
- Make strategic trust-building part of succession planning and leadership development.
- Integrate authenticity measures into ESG and corporate responsibility reporting.
Humans vs. Simulation — The Distinction
The line is clear:
- Humans possess the capacity for lived, embodied value-driven empathy.
- AI offers patterned simulation of understanding. Convincing, at times, but without embedded connection, responsibility or accountability.
Related Article: How Human Employees and AI Agents Can Collaborate Safely and Efficiently
Framework: The Human Intelligence Stress Test (Expanded)
Level 1: Automate what is repetitive — scheduling, data processing, basic analysis.
Level 2: Safeguard what impacts people — customer service, healthcare advice, employee support.
Level 3: Lead where trust, identity or strategy is at stake — policy, ethics, governance, reputation.
Level 4: Audit continuously — monitor performance using indicators such as complaint reduction, well-being outcomes and trust scores.
Level 5: Escalate transparently — establish clear processes for halting or correcting AI deployments that breach ethical boundaries.
Framework Crosswalk: The Human Intelligence Stress Test aligns with global standards.
- Levels 1-2 correspond with the EU AI Act’s “limited and high-risk” categories.
- Level 3 aligns with “unacceptable risk” zones requiring explicit human leadership.
- Levels 4-5 echo NIST’s “Govern, Map and Measure” functions, as well as ISO/IEC 42001 provisions for continuous monitoring and escalation.
This ensures the framework can be adopted alongside recognized international models.
The Call to Action: Build Genius, Not Do Genius
The genius of tomorrow is not about replicating what machines already excel at. It is about cultivating the genius only humans can sustain:
- Empathy that feels.
- Creativity rooted in lived experience.
- Adaptability shaped by uncertainty.
- Purpose and connection that extend beyond the self.
This is the genius machines cannot touch. This is the genius worth protecting.
What Does this Mean for Organizations?
- Build frameworks of trust that make authenticity operational.
- Protect human judgement as a strategic asset.
- Embed sustainability measures into AI governance.
- Treat digital trauma prevention as a central part of organizational resilience.
- Apply the Human Intelligence Stress Test as standard practice in all AI deployments.
Keeping the Door Open
These tools and frameworks are not endpoints; they are starting points. Implementing them in practice requires leadership that can navigate cultural nuance, regulatory complexity and human impact. No checklist alone can achieve that.
The value of this work lies not only in having principles on paper, but in how they are adapted, tested and lived within organizations. That is where dialogue, collaboration and continued engagement become essential.
Leaders reading this are invited to treat the Stress Test, KPI glossary and the trauma lens as prompts to pilot, adapt and refine. The real work lies in the conversations they spark — about identity, trust, resilience and responsibility in an AI-driven world.
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