Man's Search for Relevance

The Personal Side of the AI Revolution

(  The diagram above ties all the individual essays together, it's helpful to keep it in mind as you read through. 

Complementing this diagram and a necessary reading before proceeding with any essay in the publication, including this one, is the Reader's Guide. It is aimed at helping readers understand some of the concepts developed throughout the entire publication and avoiding repetition between the individual essays. Please look at it now, if you haven’t already; you can also review the guide at any later time through the top menu on the publication's home page. 

If the Reader's Guide functions as a Prologue, the post Personal AI Assistant (PAIA) functions as an Epilogue; in that post, we begin to construct a formal approach to democratic governance based on the PAIA. We may even go out on a limb and attempt to pair that democratic governance with a more benign form of capitalistic structure of the economy, also via the PAIA. 

There are two appendices to the publication, which the reader may consult as needed: a List of Changes made to the publication, in reverse chronological order, and a List of Resources, containing links to organizations, books, articles, and especially videos relevant to this publication.

The publication is “under construction”, it will go through many revisions until it reaches its final form, if it ever does. Your comments are the most valuable measure of what needs to change. )

---

In the diagram above, we cover the Participate arrow in the Free Will and Democracy article, the Support arrow in the article Democracy and Human Values, and the Align arrow in the AI Language Models as Golems article. In this article, we cover the Grow arrow. How can an AI that is aligned with human values, and supported by democratic governance, help us Grow as individuals, while in turn, we participate in that democratic governance through our free will?

Relevance - The New Human Motivation

What does it even mean for AI to help us grow? We would obviously need a measure in order to gauge this “growing”. In searching for such a measure one is forced to figure out what essentially motivates humans in this new age of AI and how AI can help increase that measure of motivation.

The Shift from Traditional Psychoanalytic Views

The three traditional psychoanalytic schools from Vienna, despite their foundational insights, seem inadequate to give us such a measure in today's digitally-driven context. Unlike the Freudian, Adlerian, or Franklian focus on pleasure, power, or meaning respectively, the modern individual gravitates toward a search for relevance, profoundly influenced by this digital context.

The mirror of social media, with its 'posts' and 'likes' and 'follows' has reshaped our perception of self-worth and societal value. This new perception is nurturing within us a stronger existential need for validation and acknowledgment, a need that transcends the explanations given by traditional psychoanalytic theories.

Before we analyze the various components of relevance, we should observe that this search for relevance is present in all humans, regardless of their cultural or geographical background. All humans desire to be significant in various spheres of life, from intimate family relationships to broader societal connections.

Just to be clear, the relevance we have in mind is not what psychologists refer to as the problem of relevance. That problem is more general and all living things must somehow solve it in order to survive. It is usually described as follows.

All living things exist in a world full of potential meaning that they cannot fully understand. The relevant information in any situation is often hard to find, unclear, and incomplete. Therefore, most problems living things face in an uncertain world are not well-defined. To survive and grow in this uncertain world, they need to figure out which facts in their environment are most relevant to them. This need is known as the problem of relevance, and it is a fundamental problem of life.

We do not refer to that fundamental problem, but rather to the smaller and more specific relevance of humans to each other. Our concept of relevance refers to the core of human motivation, and it is best understood by contrast with the three traditional psychoanalytic schools from Vienna.

Understanding Relevance

Contrasting with Viennese Theories

The image above shows relevance at the core of human motivations, as compared with the three Viennese schools. Compared to the search for relevance, searching for pleasure is too raw as a central motivation, while the search for meaning is too lofty.

The Adlerian theory of power is the closest to a theory of relevance, as both emphasize the individual as part of a collective. In both theories, humans are primarily nodes in the social graph. But the social graph is much larger now, as the family and friends in Adlerian theory have been considerably augmented by online “followers” and “Facebook friends”.

Moreover, as opposed to Adlerian theory, we are thought to be striving for relevance to others, not superiority to others. Any sign of a search for “superiority” on social media is met with dead silence, the most cutting marker of disapproval. Adlerian theory also assumes that an individual is willing to spend considerable time recollecting early childhood memories and involving family and friends in that recollection. And time and patience are in short supply nowadays.

Relevance is in the middle of the motivational wheel, more realistic, and easier to work with. As with many other such questions, there is no way of proving this centrality of relevance. We will take it as an axiom, just as we take the existence of free will as an axiom (see the Free Will and Democracy article).

Why the axioms? The eventual necessity to align AI systems with regulations will demand the design of formal systems, wherein such axioms play an essential role. We end each post with this idea of at least having an axiomatic system in mind if implementing one seems far at this time.

Centrality Does Not Mean Universality

We pinned much of this quest for relevance on the growing influence of social media. Much of this growth comes from the use of artificial intelligence. AI enables social media to analyze vast amounts of data to understand user behavior and trends and to deliver personalized experiences, like content recommendations and advertising.

But not everyone is (or will be) under the influence of social media and AI and not everyone will be driven by this quest for relevance. So, the statement that relevance is central to human motivation is a statistical statement, i.e. it applies to most but not all. Some people will continue to be centrally motivated by other factors, for example, by one of the three Viennese factors: pleasure, power, and meaning, rather than relevance.

The Components of Relevance

Relevance has three components, encompassing not just our relevance to others, but their relevance to us, and our self-relevance. Still, all three revolve around the pivotal question: "Do I matter?" These components of relevance and the terminology we use in the rest of the article are shown below. We will refer to Relevance To Others and Of Others as forms of External Relevance, and to Self-Relevance as Internal.

In the context of this innate desire to matter, every 'like' or 'follow' is a nod of approval, a modern-day accolade contributing to one's sense of self-worth and identity. The addictive nature of these social media engagements speaks to their profound psychological impact; they have become the currency of modern social relevance. You may think that this is just a temporary fad, but it’s more probable that the dependency of our lives on social technology will only increase.

Different Layouts of The Three Components

Individuals show different measures of relevance and also different layouts of their relevance as seen below. At the same time, it should be noted from the outset that the three components of relevance are interdependent. For example, we learn on social media that to be relevant to others, we have to reciprocate and let others feel that they are relevant to us.

I am neither a psychologist nor a psychoanalyst, not even a philosopher, so I pass no judgments and have no explanations here as to why a certain relevance structure may look healthier than another.

And so now that we brought relevance as the measure we needed, our original question “What Does it Mean For AI to Help Us Grow?” can be answered: AI will help us find relevance, i.e. relevance to others, the relevance of others, and most importantly, our self-relevance.

The rest of the article is dedicated to a more detailed analysis of the concept of relevance and elaborating on the answer given above. Keep in mind though that what we call growth of relevance for an individual is seen mostly through the eyes of that particular individual. He/she is the one looking for relevance.

There may be a good sense of societal relevance (how society might “objectively” evaluate an individual’s relevance), and although this societal relevance could be measured by the same methods of graph theory that we will present below, we have no interest in that type of measurement here. Such a societal measuring could easily degenerate into dystopia, whereas the measurement we have in mind is done under the control of the individual.

External Relevance: To Others and Of Others

The weights of these two components of external relevance depend on personality traits. Some people naturally seek recognition and validation from others, placing great importance on their external image and how they are perceived. Conversely, others may prioritize deep, meaningful connections where the significance of others in their lives is more valued.

The weights also depend on cultural influences: different cultures emphasize varying aspects of interpersonal relationships. Some cultures may place a higher value on individual achievements and social status, leading to a greater desire for personal significance. Others might focus more on community and collective well-being, where the significance of others is more valued.

Personal experiences, including upbringing and life events, obviously shape how we view our relationships with others. Those who have experienced strong support networks might value the significance of others more, while those who have felt the need to prove themselves might seek to be more significant to others.

Our need for personal significance versus the significance of others can also vary in different social contexts. For example, in a professional setting, one might seek more personal significance, while in family and close friendships, the significance of others might take precedence.

And finally, as people age and mature, their priorities can shift. Younger individuals might focus more on establishing their own significance, while older individuals might place more value on deep and meaningful relationships.

The Turn towards Self Relevance

We predict that the current era, dominated by social media and AI, will push individuals toward a greater pursuit of self-relevance. We are not there yet, and it may take a long time if this prediction proves to be correct at all. Several factors underpin this prediction:

Digital Fatigue and the Quest for Authenticity: In an age where social media drives the relevance to and of others, people will increasingly experience digital fatigue. This fatigue will lead to a re-evaluation of the fleeting nature of online validation, prompting deeper introspection and a turn towards self-relevance. Seeking authenticity and meaningful personal growth, individuals are likely to begin prioritizing internal validation over external recognition.

Rise of Mindfulness and Mental Health Awareness: There’s a growing global emphasis on mindfulness and mental health, encouraging us to look inward. Practices like meditation and yoga, which focus on self-awareness and inner peace, are now more widespread. These practices also point to a move towards valuing self-relevance, as people are placing more value on nurturing their mental and emotional well-being.

Technological Advancements Leading to Personalized Experiences: AI and other technological advancements are increasingly capable of offering personalized experiences. This individualization in technology use can support a turn towards self-relevance. For example, as AI technologies become more sophisticated in understanding and responding to human emotions and behaviors, AI-powered mental health apps can provide personalized therapeutic experiences, encouraging users to reflect on their internal state.

Cultural Shifts Toward Individualism: In many societies, there is a noticeable shift towards individualism, which inherently encourages people to put more value on their unique identity and personal journey. This cultural change is likely to support a movement toward seeking self-relevance, as it aligns with the notion of finding one’s own place and purpose in the world independent of others.

Overcoming the Limitations of External Validation: As people become more aware of the limitations and ephemeral nature of external validation (such as likes and followers), there's a natural gravitation towards seeking more stable, internal sources of fulfillment. Self-relevance offers a more enduring sense of worth and achievement, not reliant on the often fickle opinions of others.

Philosophical and Spiritual Exploration: There’s an increasing interest in various philosophical and spiritual traditions that emphasize self-discovery and inner fulfillment. From Eastern philosophies advocating for introspection and detachment from materialistic desires to Western existential thought encouraging self-actualization, these frameworks provide intellectual and spiritual support for the pursuit of self-relevance.

The Paradox of Choice in a Hyper-Connected World: The overwhelming array of choices and the bombardment of information in our hyper-connected world can lead to a paradox of choice, where too many external options cause stress and confusion. This can also motivate a turn inwards, as people seek clarity and peace in their internal world.

Exposure to Diverse Perspectives through Global Connectivity: Paradoxically, the global connectivity facilitated by AI and social media can also lead to a greater appreciation of diverse perspectives and, consequently, a deeper understanding of oneself. This exposure might inspire individuals to explore their values and beliefs more deeply, enhancing their search for sources of self-relevance.

Relevance in Philosophical and Cultural Contexts

Relevance Seen through Western Viewpoints

Relevance and Viktor Frankl’s Search for Meaning

When I first read Frankl’s book “Man’s Search for Meaning”, I was very much impressed, as most people are. That initial feeling has gone away as I read more about Frankl the Man and the controversies related to some of his work. I don’t want to digress into the whys and the hows of this newly found discomfort. But the book now looks a bit triumphant and imperious to me, as well as forced. I inserted the clip below as being appropriate not just for this instance, but for the entirety of the article, as our search for relevance seems to be more successful when it occurs naturally than when it is forced.

Relevance and Abraham Maslow’s Hierarchy of Needs

Maslow's theory posits that human motivation is based on a hierarchy of needs, starting from basic physiological necessities to the need for self-actualization. In today's digital age, particularly with the advent of AI, this hierarchy has taken on new dimensions. While basic needs remain constant, the ways in which social and esteem needs are met have evolved. Social media platforms, driven by AI algorithms, have become significant in fulfilling (or giving the illusion of fulfilling) these needs, particularly for belonging and esteem. But the question remains whether these digital interactions truly satisfy deeper human needs or merely offer a superficial sense of fulfillment, potentially hindering the journey towards self-actualization.

Relevance and Friedrich Nietzsche’s Existentialism

Nietzsche's existentialist thought, centered on the idea of "will to power" and the creation of one's own values, provides a more helpful framework for understanding the pursuit of relevance in the AI era. Nietzsche’s encouragement of self-overcoming and the creation of one's own identity can be paralleled with the way individuals curate their digital personas.

However, this curation, often influenced by AI algorithms and social norms, might contradict Nietzsche's ideal of authentic self-creation. Instead of forging unique paths, there's a risk of succumbing to homogenized, algorithmically determined identities. Nietzsche’s philosophy prompts a critical examination of whether our online pursuits for relevance reflect genuine self-actualization or surrender to the 'herd mentality' he cautioned against.

Relevance Seen through Eastern Viewpoints

We have seen that the Western approach to understanding human motivations often emphasizes a structured hierarchy of needs and a quest for precise rules, akin to the geometric precision of an Egyptian pyramid. In contrast, Eastern philosophy takes a more fluid, contemplative approach, seeing the human condition more as a circle than a pyramid, a circle to be explored rather than a problem to be solved.

Eastern Philosophies, Contemplative Insights, and Internal Relevance

Eastern philosophies offer a path to internal relevance that counters the constant chase for external relevance. This path supports the prediction we made above for a turn towards self-relevance.

Buddhism and Taoism offer a contrasting perspective on human motivation, emphasizing the importance of inner peace, balance, and detachment from egoic desires. In the context of AI and social media, this perspective can be particularly salient. The relentless pursuit of online relevance can be seen as an attachment to the ego and a source of suffering.

Self-Relevance and Alan Watts’ Search for Genuine Fulfillment

Alan Watts, a modern philosopher known for interpreting and popularizing Eastern philosophy for a Western audience, helps us veer away from the two external forms of relevance and toward internal relevance, understanding one's place in the universe, and the pursuit of genuine fulfillment.

Watts' philosophy, deeply rooted in Zen Buddhism and Taoism, emphasized the importance of living in the present moment and understanding the interconnectedness of all things. He often spoke about the pitfalls of living for the future or being overly concerned with societal expectations, which could be seen as a critique of modern society's obsession with external validation.

This turn towards internal relevance is mostly taking place in the present moment whereas external validation has to wait for future confirmation by others.

Measuring Relevance

How does the personal AI assistant measure the components of its citizen’s relevance? The answer is a bit technical but we should nevertheless mention it briefly, otherwise the question of measuring would be left dangling.

As we mentioned above, we are nodes in a social network. A social network is an example of a data structure known as a property graph. Such a property graph looks like the following:

A property graph is composed of nodes and arrows (also known as relationships) between these nodes, with each node and arrow having a type, the type being a collection of properties. The graph above has three nodes, all of type Person. There are three relationships in this graph, all of them of type FOLLOWS. The Person nodes will have properties, like name and age. The relationships also have properties, for example, the FOLLOWS relationship has a date property, showing when the following started.

In a real-world graph, there are many more types of nodes (Occupation, Hobby, Education, etc.), many more types of relationships (COLLEAGUE_OF, PARENT_OF, LOVES, WORKS_AT, etc.) and each of the nodes and relationships has many more properties (date_of_birth, country_of_birth, sex, current_location, etc.).

The processing of these graphs is done with some of the most important algorithms of computer science. Our point of view, since we are interested in AI done on large graphs, is that the two kinds of algorithms, graph algorithms, and AI algorithms, are usually used side-by-side, and together they produce additional information, which information can then be stored back into specific properties of the nodes and the relationships between the nodes. So you can think of AI as enhancing the graph with properties it learns through statistical analysis, while the graph algorithms are enhancing the graph with properties that reflect the topology of the graph.

Graph centrality measures are calculated by algorithms used in graph theory to measure the importance of nodes within the graph. There are many such centrality measures, each of them suitable for specific situations. Measuring relevance means using a combination of such centrality measures, done on a “merging” of all the graphs that have the individual as a node.

Centrality Measures from Cambridge Intelligence

Is this Measuring a Dystopian Kind of Big Brother Endeavor?

It can be, and in authoritarian countries, it already is. But everywhere, information about us is being collected and measurements based on that information are calculated, on social media and all other online places where we are active. That information and those measurements are however not under your control. The idea is to have your PAIA allow you to regain that control. This looks complicated but the alternatives are even more so.

Conclusion: Our Primary Search is for Relevance and AI Will Help Find It

The concept of relevance, central to our motivations, finds a new ally in AI. This partnership, nurtured with mindfulness and introspection, holds the potential to steer our journey toward a deeper understanding of ourselves and our place in the world, possibly leading us back to the unburdened relevance we experienced in childhood.

AI with its data-processing prowess offers new insights into our motivations, bridging gaps in understanding and enhancing our global interconnectedness. It can facilitate our self-discovery, build empathy towards others, and amplify our contributions to the world, aligning us with the core human quest for relevance.

(  Just like all posts have the same diagram at the top, they also have the same set of axioms at the bottom. The diagram at the top is about where we are now, this set of axioms is about the future. 

Proposing a formal theory of democratic governance may look dystopian and infringe on a citizen’s freedom of choice. But it is trying to do exactly the opposite, enhancing citizen's independence and avoiding the anarchy that AI intrusion on governance will bring if formal rules for its behavior are not established.

One cannot worry about an existential threat to humanity and not think of developing AI with formal specifications and proving formally (=mathematically) that AI systems do indeed satisfy their specifications. 

These formal rules should uphold a subset of democratic principles of liberty, equality, and justice, and reconcile them with the subset of core human values of freedom, dignity, and respect. The existence of such a reconciled subset is postulated in Axiom 2. 

Now, the caveat. We are nowhere near such a formal theory, because among other things, we do not yet have a mathematical theory explaining how neural networks learn. Without it, one cannot establish a deductive mechanism needed for proofs. So it will be a long road, but eventually we will have to travel it. )

Towards a Formal Theory of Democratic Governance in the Age of AI

• Axiom 1: Humans Have Free Will

• Axiom 2: A consistent (=non-contradictory) set of democratic principles and human values exists

• Axiom 3: Citizens are endowed with a personal AI assistant (PAIA), whose security, convenience, and privacy are under citizen’s control

  

• Axiom 4: All PAIAs are aligned with the set described in Axiom 2

• Axiom 5: A PAIA always asks for confirmation before taking ANY action

• Axiom 6: Citizens may decide to let their PAIAs vote for them, after confirmation

• Axiom 7: PAIAs monitor and score the match between the citizens’ political inclinations and the way their representatives in Congress vote and campaign

• Axiom 8: A PAIA upholds the citizen’s decisions and political stands, and never overrides them

• Axiom 9: Humans are primarily driven by a search for relevance

• Axiom 10: The 3 components of relevance can be measured by the PAIA. This measurement is private

• Axiom 11: Humans configure their PAIAs to advise them on ways to increase the components of their relevance in whatever ways they find desirable

• Axiom 12: A PAIA should assume that citizen lives in a kind, fair, and effective democracy and propose ways to keep it as such

More technical justification for the need for formal AI verification can be found on the SD-AI (Stronger Democracy through Artificial Intelligence) website:

• SD-AI’s program to verify AI formally

• articles related to this formalism are stored in SD-AI’s library section