Kalle reflects on AI, knives and money

Kalle reflects on AI, knives and money

 

The real question is not whether AI is powerful. The real question is whether those who develop, govern and use it deserve our trust.

 

 

Takeaway for leaders at all levels everywhere

Part of the answer is so obvious that it may seem hardly worth discussing. Most people already understand that AI is fundamentally a tool, much like a knife. Admittedly, it is a uniquely powerful tool whose effects may extend far beyond the intentions of any single user. Yet the core question remains remarkably familiar.

It is not primarily about the tool itself. It is about the people who develop it, govern it, use it, and the purposes they choose to serve.

The real question is therefore about trust—the overall guiding principle of social sustainability.

Science has consistently shown that three dimensions determine whether an individual deserves trust. They are the capacity to:

More interesting conclusions about our relationship with AI emerge when these three dimensions are explored together.

In the context of AI, this means using knowledge responsibly in service of a moral purpose and remaining committed to that purpose even when powerful temptations arise. Today, the most concerning challenge is not primarily the first two dimensions. It is the third one: benevolence.

But let us briefly consider all three.

A knife provides a useful analogy.

 

More in detail

A knife used in a robbery versus a knife used by a skilled surgeon is enough to begin exploring the question.

A knife carries no purpose of its own. The purpose lies in the hands of the user. Yet even a skilled surgeon may, under certain circumstances, be tempted to abandon service to the common good. The central challenge is therefore not the knife itself but the knowledge within the discipline where it is used and the intentions guiding its use.

The same applies to AI.

For anyone who has become accustomed to working with AI, its usefulness for constructive and dignified purposes is increasingly obvious. The possibility of improving decision-making, learning and problem-solving through rapid access to relevant information in service of the common good speaks largely for itself.

In my own work, AI has become an invaluable companion when testing whether scientific conclusions regarding sustainability can withstand scrutiny from many different angles and in the light of vast amounts of information available across the worldwide web.

This brings us naturally to the second dimension of trust.

Without serious knowledge, acquired through study and practical experience, how can anyone adequately evaluate a tool?

A well-meaning but insufficiently knowledgeable surgeon may still do more harm than good. Not to speak about surgeons not even meaning well for patients when they are completely vulnerable and relying on good intentions and knowledge from the doctor. The same is true when applying AI. The decisive issue is not primarily knowledge about AI itself, but knowledge of the discipline in which AI is being used.

Assuming you already possess substantial expertise in the area you wish to explore, does AI help you arrive at better conclusions? Or does limited knowledge within your field make you vulnerable to being misled by confident and elegant AI-generated responses? Can you distinguish robust patterns from exceptions, signal from noise, and evidence from speculation?

In my own work, including the development of resources through www.stepwise.global , I ensure that AI support is guided by serious knowledge of the scientifically validated principles of the FSSD Operative System and by search structures aligned with that framework. However, this is only the first step. The second is to apply judgment and experience to evaluate the quality of the AI-generated results.

On our homepage we also publish podcasts consisting of dialogues between two AI-generated voices discussing my “Kalle reflects” texts on contemporary topics. Both the original reflections and the podcasts are guided by the principles of the FSSD Operative System, connecting AI-supported inquiry to decades of research and practical experience in strategic sustainable development.

Interestingly, the result is not only that listeners may learn from the AI-generated discussions. I often find that I understand a topic more deeply after listening to the dialogue, despite having written the original manuscript myself. At the same time, misunderstandings generated by the AI has revealed weaknesses in my own instructions a number of times, including assumptions or formulations, thereby identifying opportunities for improvement.

The generative AI assistant improves through this process.

And so do I.

The first two dimensions already provide some insights  that may come across as valuable. Yet it is the third dimension that ultimately determines whether the first two become constructive or destructive.

Benevolence, as used here, does not merely mean being kind. It means maintaining commitment to the common good when personal gain points in another direction.

Knowledge and good intentions are important, but they may be abandoned when status, power, convenience or ideology enter the picture. Money often becomes a powerful vehicle through which these temptations are amplified and pursued. The larger the economic stakes, the greater the risks.

At the individual level, this is a matter of ethics and personal responsibility. It is therefore beneficial for people to cultivate both character and discipline, qualities that are essential for acquiring knowledge and using AI wisely.

So, when the economic stakes become enormous—as they increasingly are today—individual morality alone is not sufficient. We then enter the systemic domain.

 

In today’s world, the pursuit of markets, natural resources and territory has become so dominant among too many leaders that ethical reflection within geopolitics, democracy, religion, business and other societal arenas often receives diminishing attention.

Under such circumstances, trust cannot rely solely on the virtue of individuals. It also depends on the structures within which individuals operate.

This creates an obligation to consider the five boundary conditions for socially sustainable societies and institutions at all levels. Such work basically depends on (re)design of communities, removing five overall structural obstacles to trust between people, leaders and institutions. These obstacles are well explored and validated. They are barriers related to (i) health, (ii) influence, (iii) knowledge, (iv) impartiality and (v) meaning-making. (See Kalle reflects on Social Sustainability.)

Modern AI development depends heavily on exceptionally talented innovators who are currently pushing technological frontiers at remarkable speed. There is much to admire in this. Yet the financial incentives associated with technological success have already become so large that efforts to place AI consistently in service of the common good face increasing challenges.

This is not primarily a flaw of individuals.

It is a challenge arising from systems. As an experiment of thought, just go through the five structural obstacles above to consider the growing challenges of the world as we see it today.

So, individual ethics must be complemented by supportive structures at larger community levels—from organizational policies and transparent governance to appropriate laws, norms and international agreements. All guided by the five boundary conditions for redesign provided above.

Only by combining responsible individuals with responsible institutions can society fully benefit from AI while reducing the risks of misuse.

And herein lies an often-underestimated opportunity. For people who could use AI to advance the common good within their own fields of expertise, learning how to use it wisely is becoming increasingly important.

The future of AI should not be left only to those driven by power, profit or control  of opposition.

 

Conclusion

So, to leaders at all levels: please do not fall into the trap of opposing AI simply because it is new, powerful or imperfect.

On the contrary, the growing risks associated with poor knowledge, weak judgment and questionable intentions increase the importance of using AI responsibly and contribute to its development in service of the common good.

Today, many people stand on the verge of despair as they observe an unstable, unsustainable world. They often find themselves separated into islands of politics, religion, science, media, activism, business or other communities of dialogue.

For all such groups, withdrawing from AI is neither realistic nor desirable.

If well-intentioned communities striving to improve quality of life and build sustainable societies everywhere leave AI primarily to those with less constructive ambitions, a second and avoidable problem emerges.

Used wisely, AI is an extraordinary tool for learning, creativity, problem-solving and service of the common good. It can be remarkably effective in challenging assumptions, testing ideas and deepening understanding. And it may open an opportunity for all the islands of well-meaning knowledge-searching people to merge forces at a time when this is needed the most.

Actively engaging with AI in this manner is one way of supporting scientific inquiry, ethical standards and democratic processes while remaining relevant in a rapidly evolving technological world.

 

AI may replace certain tasks and transform many professions. But it cannot replace the uniquely human responsibility for purpose, judgment and moral choice.

That responsibility existed long before AI entered the scene.

The challenge at the interface between knowledge and action is ancient. Philosophers have long warned against the naturalistic fallacy—the mistaken belief that facts alone can determine what we ought to value or how we ought to act. Science, whether assisted by AI or not, can help us understand reality and inform our choices. But it cannot replace our responsibility to choose our purpose.

 

The real threat is therefore not AI itself. The real threat is the abandonment of thoughtful inquiry in favor of simplistic moral clichés—whether those clichés take the form of blind enthusiasm or blind resistance.