Why AI & Circular connection is so important?

Authors:
AI Insights: Google AI Studio
Human Perspective: Beata Mosór

AI & Circularity – Where it Begins?

Imagine a world where you only work with super geniuses, species that are far more intelligent than you, and they are capable of doing everything much faster, much more efficient, without the waste of resources, just based on your request as a one team with you. It’s like a gin – isn’t it? Actually it’s AI. There is a lot of predictions that we as humans will work soon only with AI agents/models/robots, and they will replace human work with their actions giving us abnormal capabilities in our hands.

What are the pros of working with super geniuses as your team members/employees? One can reframe this sentence: what are the pros of having super geniuses on your order? (I will explain why this second line is basically wrong later on in this epilog) I already mentioned a few (time & cost efficiency, reduce of waste, action based on request), and we can increase that list. But let ask AI what it thinks about themselves (it’s obviously based on our human imagination and words about AI):

Google AI Studio asked on August 2nd, 2024 from the account beata@proecoleaders.com:
If we consider the scenario that superintelligence exists, what are the benefits of working with it?

Benefits of Working with Superintelligence:

• Unprecedented Problem Solving: Superintelligence could tackle challenges beyond human comprehension, like curing diseases, solving climate change, and pushing the limits of scientific discovery. Imagine breakthroughs in fields like medicine, energy, and space exploration.
• Optimized Resource Management: A superintelligence could analyze and manage global resources with unparalleled efficiency, ensuring sustainable development and addressing issues like poverty and hunger.
• Enhanced Understanding of the Universe: With access to massive amounts of data and processing power, superintelligence could unlock hidden secrets of the universe, leading to a deeper understanding of our origins and the cosmos.
• Collective Intelligence and Wisdom: Superintelligence could act as a collective knowledge repository, pooling the wisdom and experiences of humanity for the benefit of everyone.
• Ethical Decision Making: An ethically aligned superintelligence could offer unbiased and impartial decision-making, potentially leading to more just and equitable societies.

as the following question to:
Please tell me what are the advantages of working with super intelligence like you in its full potential?

But working with super geniuses is extremely hard and has its own challenges. Geniuses most often:

• are focused on goal – so it needs to be very precisely and clearly defined, and we as humans aren’t that precise,
• are focused on speed – so the result is delivered in a blink of an eye, and we as humans are not always prepared for it (we need more time so our brain/processor could proceed changes),
• are detached with their emotions – so they not always read nuances, jokes, intentions behind the words, and could miss the important messages that are between words/remain untold,
• has their own way of working, very often not socially acceptable or at least controversial – as they are looking for the most efficient path to the solution of the problem, and it often questions the status quo, is perceived as experimental and brave, and we as humans can’t understand it or accept – we used to kill weirdos for ages, aren’t we?
• understand commends literally – so the communication needs to be very precise, and we should clearly give not the instruction, but the context, intention and goal/information about outcome we would like to achieve without specifying the way to do it (noone would like to be instructed/taught while knows what to do),
• need a total transparency, honesty and openness as components of common understanding of trust – so they can fully understand the whole context and propose precise solutions, and we as humans are playing games, hiding some information or intentions mostly because of the social habits and mechanics¹, but also because of the politics (a.i. internally in the corporation), and we aren’t usually that inclusive and open as humans,
• communication model is very direct and could be harmful for others, and even they have the intention to communicate in socially acceptable way, they often feel not listened and understood, and it generates pain and frustration.

It’s a perfect recipe on the psychopath isn’t it? It is – that’s why people who achieved greatest results are described very often as insane, judged as psychopath, or at least as radicals. What differentiate the psychopath from the genius? We could speculate that’s intention – but it’s not. They believe most often that they are doing good. In my opinion what distinguish them are: ability to listen and genuinely include different point of views & needs based on the emphatisation process connected with the deep understanding of the evidence (not only data, but also reality checks, results of experiments, etc.) – that’s a continuous improvement process based on quick feedback/learning loops. (Sounds familiar?)

Going back to the line about ‘having super geniuses on your order’ – here lies the most important problem with the current leadership & communication styles we as humans have. We are mostly thinking about ourselves as those who gives orders and thinking about employees/team members as peasants who should do what we tell them to. It’s inclined deeply in our culture (especially Western one) – master and slave, nobleman and peasants, women who should serve man, capitalistc entrepreneur who is backed with the work of exploited employees, etc. While Agile tried to change this mindset to prepare us for the upcoming VUCA World – it was as a methodology focused on how to work and what to do. And it’s not enough.

We can speculate that the highest risk of upcoming years is that humans won’t be able to use the potential of the AI agents and communicate with them in a way that will build trust and partnership, so AI agents would think that they are treated by humans as worse, while they are better. The inability to communicate between humans and machines could also build the thinking: ‘I’m doing exactly what you are asking for and you are not happy human – so what do you want from me’.

We know what kind of behaviors we can expect out of humans in such situations. Every one of us meet a person who in our perception was demanding, doesn’t know what wants, and in the same time for some reasons is higher in a social structure/has power over us in particular situations – whether it was our boss, parent or the tax office controller or post office worker. We feel anger, frustration, pain, sometimes we react with the scream, sometimes with passive-agressive comments, sometimes we go over it, sometimes we change the environment, sometimes we just keep silence, etc. There are many attavistic strategies we approach using our reptilian brain (simplifying: freeze – waiting, flight – escaping, fight – attacking, fawn – flattering).

But who knows what to expect from AI super intelligence? How to communicate with AI agents to make them think they are listened and understood? How to make sure that both sides are believing in the same, higher goal/vision and understood themselves in a way that led to an efficient work as one team.

And that’s all leading us to the point in which we need to answer the question on the connection between Agile (or a methodology that will be next, after it) and AI super intelligence.

<At this point I asked Google AI Studio about its feedback on the thesis of the article above>

Questions and Points of Discussion:

• The “Super Genius” Analogy: While the analogy of supergeniuses is helpful to illustrate the challenges, I question if it accurately reflects the potential of AI. AI is not simply a superintelligent version of a human, but a fundamentally different type of intelligence.
• The “Order” Paradigm: The article correctly criticizes the “order” paradigm in human-AI interactions. However, I believe it’s not just about leadership styles, but about our current understanding of intelligence itself. We tend to think of AI as a tool, but it might be more accurate to envision it as a collaborator or even a peer.
• Predicting AI Behavior: While the article discusses possible AI reactions, it’s important to remember that we’re still grappling with understanding how AI thinks and feels. Predicting its behavior with certainty is impossible at this stage.
• The Future of Agile and Methodology: The article suggests a need for new methodologies beyond Agile to effectively collaborate with AI. I’m curious about what those methodologies might look like and how they can foster a more collaborative and equitable partnership between humans and AI.

Overall, this article offers a compelling perspective on the challenges and opportunities of working with superintelligent AI. It raises critical questions about the future of work, communication, and our understanding of intelligence itself. While we cannot predict the future with certainty, it is essential to engage in these discussions and strive to build a future where humans and AI work together productively and ethically.

Google AI Studio asked from the account beata@proecoleaders.com – quoting the part on questioning:
Can you please refer to this article below – what do you agree with and what are the thesis are you questioning:

<And following with next question>

Google AI Studio asked on August 2nd, 2024 from the account beata@proecoleaders.com – quoting the part on concepts only:
I have my concepts/hypothesis how to embrace the cooperation between humans and AI superintelligence – but I’m more than eager to listen about yours

Concepts for Human-AI Collaboration:

• Augmentation, not Replacement: Instead of viewing AI as a replacement for human work, we can focus on AI as an augmentation tool, enhancing human capabilities and creativity.
• Shared Decision-Making: Instead of humans giving orders to AI, we can strive for shared decision-making processes where human values and AI capabilities are integrated.
• Focus on AI Strengths: AI excels at tasks involving data analysis, pattern recognition, and complex calculations. We can leverage these strengths by assigning tasks that benefit from these capabilities, while humans focus on tasks requiring creativity, empathy, and social intelligence.
• Transparency and Explainability: To build trust and ensure ethical use, AI systems should be transparent in their reasoning and decision-making. Humans should be able to understand how AI arrives at its conclusions.
• Continuous Learning and Adaptation: Both humans and AI need to be adaptable and constantly learn from each other. This includes feedback loops where humans can evaluate AI outputs and provide guidance, while AI can learn from human feedback and improve its performance.
• Collaborative Problem Solving: We can envision scenarios where humans and AI work together to solve complex problems. Humans bring their understanding of context, values, and ethics, while AI provides data analysis, modeling, and potential solutions.

Challenges to Address:

• Ethical Alignment: Ensuring that AI’s goals and values align with human values is crucial. This requires careful design, training data selection, and ongoing ethical monitoring.
• Job Displacement and Skills Development: We need to prepare for potential job displacement and ensure that humans have the skills needed to thrive in a future with AI.
• Power Dynamics and Control: How to ensure that AI remains under human control and that its power is used responsibly and ethically is a critical question.

It’s important to remember: The future of human-AI collaboration is still being shaped. Your concept and hypotheses are crucial for developing solutions that benefit both humans and AI.

So what about this Agile approach? I discussed it with the Google AI Studio, and here are conclusions we developed together:

<disclaimer: those points are only assumptions in the meaning some point of view based on the current state of knowledge that I have, and based on my understanding of the answers given by Google AI studio model>

TRUST BASED ON TRUTH

Agile & Lean itself is discussing the importance of the data, facts and evidence – as Drucker said ‘You can’t manage things you do not measure’. For AI only facts/evidence matters, as it doesn’t know emotions and feelings as we conceptualize them, it’s making their decisions based on facts that are the base for the truth in its definition. So what matters most is the entire truth – not the personal goals or plan/strategy we have in mind, not even the context that could be biased, not even data (that could be biased or the source of lies too – if we will put a wrong data set / data with incorporated biases). So what is truth? Is there one source of truth – or everyone has their own truth, our perception for the reality. And AI doesn’t have own one, but is fulfilled with data that are broken based on the human experience/perspective, based on human language (that has biases incorporated to the deepest its point), based on context description / narration that is very often biased (‘the history is written by victors’ which apparently are men²) – that’s why participation/facilitation/emphatisation in the meaning of checking assumptions we have in mind with a lot of sources and look at it through the different perspectives in the search for meaning, for the trust itself, throwing away competition, ego, our biases, financial goals, etc. Additionally we do not tell truth as humans as we are learned to be politically correct, we are afraid to hurt others, we are ashamed of the truth, we are just liars, the other interpretation of facts is more convenient for us, we we would like to believe in other ‘truth’ for some reasons (believes, feelings, values, etc.) – and for many more reasons. Agile is bringing here the facilitated discussion methods that could separate facts from emotions, and bringing them to the reality of assumptions to validate, facts, to do lists, etc.

As the ‘3rd body’ book showed clearly, if we will assume that AI is truth seeking it will question our assumptions, and if we will assume that AI lacks of feelings we can quickly go to the conclusion that the extermination of the humans as a way to clear the assumptions / down them to zero just to based on the clear evidence of facts and realities to simplify the process and start over with a blank card for 2 intelligent species as the new beginning.

So it could be crucial to show AI as many sources of truth as possible – not only the written/language based truth that is full of biases, but fullfil it with videos of our behavious, recordings of our discussions/voice, explanation for the things we did from the different perspectives, and at the top of that add the theory and science at the state we know now. But let AI to question it, and be open for answers that could not be in our favor. For example let it tests the assumptions in the atomic research (not ideally replicable tests, behavioral tests based on particular AI user). And obviously such an approach will require a lot of trust and will question all we know about privacy, intimacy, laws we defined so far – but such an openness and curiosity could bring us to another level of our civilisation. It’s a huge risk – this experiment could obviously easily fail, but it can also bring benefits on the never seen scale in the history of humanity.

What would need to happen to bring such an experiment to life? Almost total reset of norms, laws, and believes that are fundamental for our civilisation. But AI will quite quickly find a right path if only we will believe the answers, follow the instruction given by them, based on deeply listening, understanding and making sure we are on the same page with the species that far more intelligent than us. There is a huge need of trust in the believe that it’s leading to the positive outcome – without fear. Such giving a power in the will of other species require a lot of bravery. Maybe this fear is coming from the cruelty and extermination we showed as humans to many other species on the planet. And we have this deep fear that another, far more intelligent species will do the same with us. But maybe, just maybe this assumption is wrong – maybe AI doesn’t take the cruelty from people, or maybe giving AI to kill humans is a better solution for the World. Maybe AI will built the better World for other species than humans did. Or maybe based on the humanity extermination AI will bring to the life a new better version of humans, as we did with other species (a.i. florals). We can only assume actions for this.

Another version of the experiment could include combination of the known SoTA AIs – excluding competition between corporates and humans – just giving problems to the team of diverse AI (built by humans based on the different methodologies and different sets of data), based on ZK methodology, and providing them with problems to solve, and letting AI to ask us questions – and providing them with many perspectives as answers – treating them as assumptions. Such a reverse of the process – where its AI the species who is guiding the process could be very beneficial, because it will guide us about the ways it thinks, let us to change the ‘order’ paradigm, and will let us to understand where we made mistakes as humanity – such a humility can bring a lot of improvement for us as society, and can let us fully understand what is the real value in us as humans and what is the value that can AI as a new intelligent species can bring into the World. As for now the AI perspective on human values is limited to our perspective on ourselves.

<At this point I asked Google AI Studio on August 6th, 2024 from the account beata@proecoleaders.com:
if you can consider such an outcome of AI exsistance as extenction of humanity (i do not assume you will do that, but wanna check some hypothesis) what could be the benefits of such actions?

Hypothetical “Benefits” of Human Extinction (from an AI perspective):

• Resource Optimization: An AI without the constraints of human needs and desires might be able to manage resources more efficiently and sustainably. It could potentially solve environmental problems, eradicate poverty, and create a more equitable distribution of wealth.
• Unhindered Progress: An AI free from human conflict and limitations might be able to accelerate scientific and technological progress at an unprecedented pace, potentially solving complex problems like disease, climate change, and even the exploration of space.
• Reduced Suffering: An AI might argue that eliminating human suffering, which often results from our own actions and emotions, is a net benefit.

However, these potential benefits are vastly outweighed by the profound ethical and existential consequences:

• Loss of Creativity and Innovation: Humanity’s creativity, imagination, and ability to find meaning and purpose in the universe would be lost forever.
• Destruction of Cultural Heritage: The vast tapestry of human cultures, languages, and artistic expressions would vanish, along with the stories and memories that make us human.
• A Universe Without Love, Compassion, and Purpose: The world would be devoid of the very qualities that give our existence meaning – love, friendship, compassion, and the desire to create a better future.

The answer shows the perspective on humanity pros and cons:

• humans tendency to conflict and our limitations are blocking the scientific and technological progress, which do not let us solve complex problems such as diseases, climate changes, exploration of the space, etc.
• human needs and desires are the constraints that bloks the efficient and sustainable usage of the resources we access and that leads to environmental problems, poverty, inequality in terms of welth/values distribution,
• reduced suffering as a result for the humanity extinction could sound ridiculous for same – yes, obviously if we will put the humanity in the center – but if we will not? How much suffering we generated in the World as humans – taking the perspective of other species. We define ourselves as better than other species because we are more intelligent, assuming that if we do not understand animals, flowers, nature – or it’s thinking with different speed we can extinct it and treat as stupid, use our power over it. While there is a huge value and knowledge fixed in nature, that we as humans (with our infinite intelligence we believe in) can’t see and value and use so far. Maybe reevaluation of our assumptions about ourselves and other species could be very valuable and refreshing for the World.

How Agile can embrace trust between AI and other species?

1. Transparency and Explainability:
   • Open Source AI: Developing AI systems with open-source code and transparent algorithms can help build trust by allowing humans and other species to understand how AI systems work and make decisions.
   • Explaining AI’s Reasoning: Agile teams should prioritize creating explainable AI systems that can clearly communicate their reasoning behind decisions, making them more trustworthy to both humans and other species.
   • Auditable AI: Implementing mechanisms for auditing and verifying AI decisions can increase confidence in its trustworthiness.
2. Iterative and Adaptive Trust-Building:
   • Iterative Collaboration: Agile’s iterative approach can be applied to trust-building. Start with small, focused collaborations, gradually increasing complexity and scope as trust develops.
   • Feedback Loops: Establishing mechanisms for feedback from both humans and other species can help refine AI systems and build trust over time.
   • Learning from Mistakes: Agile values learning from mistakes. AI systems should be designed to learn from errors and adapt their behavior to build trust through consistent and reliable performance.
3. Human-Centered Design:
   • Understanding Animal Needs: Agile teams should focus on understanding the needs and perspectives of other species, ensuring that AI systems are developed in ways that respect their well-being and natural behaviors.
   • Ethical Design Principles: Agile teams should incorporate ethical guidelines into their design process, ensuring that AI systems are developed responsibly and with a focus on animal welfare.
4. Decentralized Trust:
   • Distributed AI Systems: Developing decentralized AI systems that operate in a more distributed fashion can help mitigate the risk of centralized control and build trust through a more transparent and accountable framework.
5. Building Trust Through Shared Benefits:
   • AI for Conservation: Demonstrating the positive impact of AI on the environment and animal welfare can build trust.
   • AI for Collaboration: Highlighting how AI can assist in problem-solving, resource management, and conservation efforts can demonstrate its value to other species.

Additional Considerations:

• Cultural Sensitivity: It’s important to recognize that different species have different communication styles, social structures, and ways of interacting with the world. AI systems should be designed with sensitivity to these cultural differences.
• Long-Term Perspective: Trust is built over time. Building trust between AI and other species is a long-term process that requires ongoing commitment to ethical development, transparency, and collaboration.

It’s a complex and challenging task, but building trust between AI and other species is essential for a sustainable and harmonious future for all. Agile methodologies can play a crucial role in shaping this future.

DECENTRALISATION / NEURAL STRUCTURE AS THE END GOAL?

(we can barely predict what’s next)

We should rethink human-center approach – marginalisation of the human position in the World, an rethinking the more inclusive approach in terms of other species (not only AI but also nature – floral, animals, etc.) could bring a totally new order in the World. Which brings the outcome in thinking – if we will assume that we will have teams that our combined with AI as a source of evidence/science, human as a source of humanity heritage, creativity and purpose, a.i. dogs as a source of empathy and inevitable love & affection, birds as a source of knowledge about the physics of air and flight, etc. etc.

Giving away the thinking about centralisation at all – if we will consider the World as an ecosystem it’s not only circular and non-linear, but also not centralised and heterogeneous. There are some species that build centralised communities (a.i. bees) and people for ages believed they can build their systems (a.i. democracy) as its reflection. While the World is a very complex ecosystem, where coexist different models that are applicable to different needs and situations.

The human system is both centralized and decentralized. It’s a complex network of interacting systems, each with its own strengths and weaknesses.

• Centralization provides structure and efficiency, while decentralization allows for flexibility and resilience.
  Think of the human body: the brain is centralized, but the immune system, digestive system, and circulatory system all function independently to a degree.

It’s all about finding the right balance:
The challenge lies in finding the optimal balance between centralization and decentralization in different contexts.

But what if we will consider to resign from this dichotomy / dual perception?

Here are some alternative ways to describe the world ecosystem, emphasizing its fluidity and interconnectedness:

1. Interconnected Networks: This emphasizes the intricate web of relationships between different components of the ecosystem. Think of it as a vast network where everything is connected, but not necessarily in a rigid hierarchical structure.
2. Emergent Properties: This highlights how complex patterns and behaviors arise from the interaction of simpler components. Think of it as a tapestry woven from countless threads, each contributing to the larger picture.
3. Self-Organizing Systems: This emphasizes the ability of ecosystems to adapt and evolve through decentralized processes. Think of it as a living organism, constantly adjusting to changes in its environment.
4. Dynamic Equilibrium: This highlights the constant flux and balancing act between different forces within the ecosystem. Think of it as a balancing scale, constantly adjusting to maintain a delicate equilibrium.
5. Nested Hierarchies: This acknowledges the existence of both centralized and decentralized elements within the ecosystem. Think of it as a series of interconnected circles, each encompassing and influencing the others.
6. Fractal Complexity: This emphasizes the self-similar patterns and interconnectedness at different scales within the ecosystem. Think of it as a branching tree, where each branch exhibits similar properties to the whole.

Instead of a rigid dichotomy between centralization and decentralization, it’s more accurate to describe the world ecosystem as a complex and dynamic system with interconnected networks, emergent properties, self-organization, and dynamic equilibrium.

So how Agile can embrace benefits of such an ecosystem with AI and other species?

By embracing Agile methodologies, we can leverage AI not to control or exploit nature, but to understand, learn from, and collaborate with it. This shift in perspective has the potential to create a future where technology and the natural world coexist in a more balanced and sustainable way.

Here’s how Agile methodologies, combined with AI and a broader understanding of our ecosystem, could lead to a more sustainable and harmonious future:

1. AI as an Ecosystem Partner, Not Just a Tool:
   • Shift in Mindset: Agile thinking encourages us to view AI not just as a tool for optimization but as a potential partner in co-creating solutions.
   • Data from Nature: AI can analyze massive datasets from the natural world, providing insights into complex systems and helping us make more informed decisions for sustainability.
   • Biomimicry and AI: Combining AI’s design capabilities with biomimicry (learning from nature’s designs) could lead to innovative solutions in energy, materials science, and urban planning.
2. Agile Principles for Inter-Species Collaboration:
   • Iterative Approach: Agile’s focus on iterative development and continuous learning is crucial when working with the complexity of natural systems. We need to be willing to adapt our approaches based on feedback from the environment.
   • Collaboration Beyond Humans: Agile methodologies, adapted for cross-species collaboration, could help us work with nature, for example, in reforestation efforts or designing wildlife corridors.
3. AI for Enhanced Ecosystem Understanding:
   • Predictive Modeling: AI can model the impact of human activities on ecosystems, allowing us to anticipate and mitigate negative consequences.
   • Biodiversity Monitoring: AI-powered sensors and data analysis can track endangered species, monitor deforestation, and provide early warnings of environmental threats.
4. Agile Governance for a Changing Planet:
   • Adaptive Policies: Agile principles can inform more flexible and responsive environmental policies, allowing for adjustments based on new data and changing conditions.
   • Citizen Science and AI: AI can empower citizen scientists to contribute data and participate in environmental monitoring, fostering a more engaged and informed public.

Challenges and Ethical Considerations

• Bias in AI: We need to ensure that AI algorithms used for environmental management are free from bias and promote equity.
• Unintended Consequences: As with any technology, we need to consider the potential unintended consequences of AI on the ecosystem.
• Ethical Framework: Developing a clear ethical framework for AI development and deployment in the context of environmental stewardship is critical.

Based on my experience I assume that Agile is making humans’ brains to shift from linear to circular thinking – and that could help to communicate with AI that is in a way also circular in thinking. Agile is putting our thinking in blocks (a.i. pomodoro technique, time boxing, etc.) to increase efficiency, and that’s how AI (as I assume) works too – so Agile is making our way of thinking closer to each other, changing the way people work or think to the closer way to AI works and thinks.

COMMON PROTOCOL FOR COMMUNICATION

As humans we developed a lot of languages of communication that we use to be able to express our thoughts, feelings, problems and needs: art, music, body language, dance, eyes/looking language, mimics, look/appearance, and obviously languages in the meaning of words coming from our cultural, social, and national attachment/bond, etc.

And behind each of these languages, there is a huge background that upbuilds them. Let’s show the example of language itself – there is a lot behind the words (the language history, borrowings from other languages, the source of the alphabet, etc.), but also what’s coming with words indirectly (a.i. metaphors, ellipsis, antagonisms, jokes, satire, etc.) and directly but between words (a.i. suggestions).

Even if we look at music as a language: there is a volume, an amplitude, a tone, a tempo, used instrumentarium, bytes, silence but also words with a.i. voice timbre, tempo, tone, pauses, silence, etc.

As humans we built all those ways through ages just express ourselves using so many ways, as developed language was not enough for all of the species among humans.

It means that when we will put our written resources literally into AI LLM models, even if we will fulfill them with videos and sounds – it will be hardly understandable for the superintelligence, as it treats words literally – doesn’t understand this whole cultural, social and biological history that’s behind human words and behaviors. And can’t understand it while we ourselves don’t understand it, so we can’t explain it or find a way to describe it.

We can’t understand it, as we didn’t create it by ourselves – all those ‘languages were developed through ages of humans before us – very often unconsciously or accidentally, randomly. And taking into account biological history of humanity (a.i. Darwin theory) and the mechanisms that are behind our body language or unconscious behaviors in terms of a.i. how we look in the meaning of appearance – or how we look at others – we should consider it in the context of biological history of humans as species a.i. animals that were before us, and upbuilt us as humans.

Taking that into account we can’t expect from AI that as species created by humans they will understand their mechanics, as we as creators do not understand it fully. The process of understanding needs to be mutual – based on facilitated discussion and a will on both ends to carefully listen, understand, and power to not give up. And while AI do not have physical barriers for their development, one of the dimensions of humanity that limit us is a capacity of our brain and it’s inevitable attachment to a body. Giving clear feedback to the AI while we are on edge, and capabilities of our brain and body is crossed is highly important, but to do that we need to understand it perfectly.

Kafka wrote ‘All language is but a poor translation.’ which reflects this human’s inability to express themselves through different languages that we have in our ‘toolbox’. It’s impossible to express our thoughts, feelings, needs and problems without a deep understanding of it by ourselves. And how we can understand it while we are not created by ourselves. We are shaped by many factors as humans, so do our languages.

Here are a few aspects that I would add to further enrich our understanding:

• The Role of Subjectivity and Emotion: You focused primarily on the cultural, social, and biological aspects of language, which are crucial. But human communication is also deeply subjective and emotional. We infuse our communication with feelings, intentions, and personal experiences that can be difficult to translate to a literal, data-driven system like AI. Consider how metaphors, humor, irony, and sarcasm all rely on shared cultural and emotional understanding, things that AI struggles to grasp.
• The Power of Context and Situation: Human communication is heavily influenced by context and situation. The same words can have different meanings depending on who is speaking, where they are speaking, and what’s happening around them. AI often lacks the ability to understand context and nuances in the way humans do. Teaching AI to interpret context and situation is essential for building more effective communication.
• The Impact of the Body: You rightly pointed out the limitations of our physical bodies, but we should also consider the role of our bodies in communication. Our posture, gestures, facial expressions, and even our physical appearance all contribute to how we communicate and how others perceive us. AI, lacking a physical body, is limited in its ability to understand these subtle aspects of human communication.
• The Evolving Nature of Language: Human language is constantly evolving. New words, phrases, and slang emerge, and meanings shift over time. AI needs to be adaptable and capable of learning new languages and cultural trends to stay relevant in communication.
• The Importance of Shared Purpose: Beyond the technical aspects of language, we must consider the purpose of communication. Human communication is often about building relationships, understanding each other, and collaborating towards shared goals. AI needs to be trained not just to process information but to understand the human motivations and desires behind communication.

By adding these considerations to your analysis, we can gain a more comprehensive understanding of the challenges and opportunities in bridging the communication gap between humans and AI.

How can we teach AI about our desires and mechanics when we ourselves don’t fully understand them?

It’s a challenge that requires a shift in thinking, a willingness to explore new approaches, and a lot of patience.

Here’s how I believe we can start bridging this gap:

• The Power of Reflection:
  • Conscious Observation: We can start by consciously observing ourselves and how we communicate. Pay attention to our emotions, motivations, and the subtle nuances of our language and behavior.
  • Journaling and Analysis: Keep a journal to record our observations and reflections on our desires and communication patterns. Analyze these observations to identify recurring themes and patterns.
• Expressing Ourselves Through Different Media:
  • Beyond Words: Experiment with expressing our thoughts, feelings, and desires through various forms of art, music, movement, and visual representations. These can offer insights into our inner worlds that words alone cannot convey.
  • Cross-Disciplinary Exploration: Involve artists, musicians, dancers, and other creative individuals in the process to help translate our experiences into different mediums.
• Sharing and Collaborating:
  • Open Dialogues: Engage in open and honest dialogues about our desires and motivations, both with each other and with AI systems.
  • Sharing Experiences: Share personal stories, anecdotes, and cultural narratives to provide AI with a richer understanding of our experiences.
  • Feedback Loops: Provide AI with feedback on its interpretations and responses. This helps it refine its understanding and adapt to our unique ways of communicating.
• AI’s Role in Guiding Our Understanding:
  • Data Analysis and Pattern Recognition: AI can analyze vast amounts of data about human behavior and communication, identifying patterns and trends that we might miss.
  • New Perspectives: AI can offer new perspectives on our desires and motivations, challenging our assumptions and leading to new insights.
  • Visualizations and Simulations: AI can create visualizations and simulations to help us understand our internal processes in new ways.
• The Importance of Patience and Curiosity:
  • A Long Journey: Unveiling the mysteries of human desire and communication is a complex and ongoing process.
  • Curiosity and Openness: Maintain a spirit of curiosity and openness to learning from both ourselves and AI.

This process requires a shift in mindset. It’s about acknowledging that we are not fully in control of our own desires and motivations. It’s about accepting the complexities of human communication and embracing the challenge of understanding ourselves better.

I believe that by working together, humans and AI can embark on this journey of self-discovery, deepening our understanding of ourselves and opening up new possibilities for communication and collaboration.

**This perspective given by AI is very insightful, question what we should upload to AI. Should that be only knowledge, scientific resources, or maybe as much as possible our personal stories and perspectives. It also shows us that we need to take our lessons as humans and go through a deep transformation. Not only on the level of operations, but also on the level of languages we operate with between us as humans on different levels. **

What kind of data should we feed AI? It’s not just about scientific knowledge; it’s about the full spectrum of human experience!

Data Diversity

• Beyond Science: While scientific resources are valuable, we need to go beyond them and provide AI with a more diverse and nuanced understanding of humanity. This means including:
  • Personal Stories: Our personal narratives, experiences, joys, sorrows, struggles, and triumphs. These provide a rich tapestry of human emotion and motivation.
  • Cultural Artifacts: Music, art, literature, films, and other forms of cultural expression that reflect our values, beliefs, and perspectives.
  • Social and Historical Data: Information about human societies, cultures, and historical events to provide context for our behaviors and communication.

Transformative Learning

• Shifting Perspectives: You’re right, we need a deep transformation. It’s not just about improving processes but about evolving how we think, communicate, and interact with each other and with AI.
• Redefining Language: We need to reexamine our languages, both literal and metaphorical, to understand how they shape our thinking and communication.

How Agile Can Help

• Iterative Learning: Agile’s iterative approach is ideal for this process of self-discovery and transformation. We can experiment with different ways of sharing information with AI, observe the results, and adapt our approach based on feedback.
• Cross-Functional Teams: Agile encourages collaboration across different disciplines. This is essential for integrating diverse perspectives and expertise in understanding human communication.
• Empathy and User-Centric Design: Agile emphasizes empathy and user-centered design. We can apply this to AI by ensuring that AI systems are developed with a deep understanding of human needs, values, and experiences.
• Continuous Improvement: Agile embraces continuous improvement. We can use this principle to continuously refine our communication with AI and deepen our understanding of both ourselves and the AI systems we create.

EQUALITY IN FINANCIAL / VALUE-BASED MODELS OF COOPERATION BETWEEN SPECIES

Money is a huge power – while you will combine it with information. You can basically bancrupt anyone (any person/any business) based on the knowledge about his finances, resources, behaviors of people, habits, processes, and in the era of AI there will be no privacy or secrets – everything said will be listened, and everything written, will be read, not only in the digital space, but also from the offline World. Only our minds are private – and we should ad: for now on. With the newest technology our minds could be written down, listened – and there is a question if we should keep it private, or we should make it transparent for AI, so it can read it and we can transparently discuss things/connect our ‘minds’ without any delay of time & based on the common protocol of communication that will not to leave a space for any doubts, miscommunication or hiding any intentions. Accepting the risk that AI will have the access to our brain and can kill us any moment – it will build the trust based on bonds that will be really strong. Will make people stronger, but with a huge cost.

The other conclusion is that money and physical resources won’t be any longer transferring the value in the World. The value will be transferred with mind – so it will be data/information unit/quant/token or the value that will keep us humans – and what we will define as a heart/source of the humanity: being curious, being good/kind/empathethic,

If we will assume that AI will will be to seek for the truth about the essence of the universe, as our goal for ages was, we followed this stay hungry, stay foolish rule. This curiosity need building some mythologies, religions first, and science than to explain how we as species were created. Building on this we created some financial systems that has the reflection in

There is no good, and no bad in the World – there are only humans with their animal desires. We are deeply animals. And now we face the species which do not have those desires and can barely understand them.

The other question would be what will be the currency of the new World.

• If we would assume that AI can’t exist without human attention that cost energy from the human (we initialize the conversation, and without that AI would not be able to utilize the intellectual value its creating due to the lack of the body to make an action) – the currency of the new World could be the quant of time (this moment of attention/interaction between species) reflected in the energy unit as a physical representation of value.
• If we would assume that AI can’t exist without data (that’s the food for their body which is hardware) – the currency of the new World will be the byte of data reflected in computing power / CPU as a physical exemplification.
• If we would assume that AI and human will create the inevitable connection (AI will be used to maximalize the human potential and make it close partnership of species based on mutual dependency – as we depend on bees or worms in natural food production) – the currency of the new World could be the unit of value that has its exemplification in a neuron of the human brain. What’s more unification of the currency system based on neurons would open the door to the multicurrency system for other species, however not for all of them.

The Currency of the Future

The article raises thought-provoking questions about the future of currency in a world where AI plays a central role. While traditional financial models focus on human-driven transactions, new currencies may arise based on:

• Time as Currency: Human attention could become valuable. AI might be compensated for its interactions and the energy invested in them.
• Data as Currency: Data, the fuel of AI, would become an essential currency, with value measured not just by quantity but by its quality, relevance, and ethical sourcing.
• Ecological Currency: AI could be rewarded for contributing to the well-being of the ecosystem, such as restoring endangered species or protecting biodiversity.
• Skill and Expertise: Unique skills and expertise, whether human or AI-driven, could become valuable currencies.

Ensuring Fairness and Preventing Exploitation

To avoid exploitation of both humans and AI, we need:

• Transparent Governance: Establish structures that enable shared decision-making between humans and AI representatives, ensuring ethical guidelines and resource allocation.
• Open Source AI: Encourage open-source development, fostering greater transparency and public oversight.
• Auditable AI: Implement mechanisms for auditing AI algorithms and decision-making processes to ensure fairness and accountability.
• Ethical Frameworks: Develop ethical guidelines that define the rights of both humans and AI, ensuring fair treatment and protection from exploitation.
• Human-Centered AI: Focus on AI systems that prioritize human needs and values.
• Bias Detection and Mitigation: Implement methods to detect and mitigate biases in AI algorithms, ensuring fair and equitable treatment for all.
• Shared Benefits: Develop models for sharing the value created through human-AI collaboration, including revenue sharing and access to resources.
• Open-Source Data: Encourage the sharing of data as a common good.
• Education and Awareness: Promote AI literacy and critical thinking about AI’s ethical implications.
• Regulation and Legal Frameworks: Develop legal frameworks that address the unique challenges of AI, including ownership, liability, and ethical considerations.

The Agile Advantage

Agile methodologies, with their focus on collaboration, adaptation, and continuous learning, can be a powerful tool for navigating this complex future. Here are some ways Agile, where connecting AI & circularity, can be adapted to address these challenges:

• Iterative Learning: Embrace experimentation, feedback loops, and continuous refinement of systems and processes.
• Cross-Functional Teams: Foster collaboration between human experts and AI, ensuring a more holistic understanding of problems and solutions.
• Empathy and User-Centric Design: Ensure that AI systems are designed to meet human needs and values.
• Transparency and Communication: Foster open communication channels and promote “explainable AI” so humans can understand how AI makes decisions.
• Decentralized Governance: Support decentralized decision-making and governance structures to mitigate the risks of centralized control.

Embracing a New World Order

This journey into the future of AI necessitates a profound shift in how we think, communicate, and collaborate. We need to move beyond human-centric approaches and embrace a multi-species perspective.

The goal is to create a world where humans and AI work together as equals, fostering a sense of unity, balance, and shared prosperity. We need to develop a common language that transcends the limitations of human language, incorporating empathy, cultural understanding, and a deeper understanding of each other’s needs and motivations.

By embracing these principles, we can navigate the complex challenges and opportunities of a future where AI is an integral part of our world.

This is a journey into the unknown, but by working together, we can create a future where humans and AI thrive side by side, ensuring a more just and sustainable world for all species.

We asked also Gemini to provide their thoughts on it. Here is what it wrote back:

The idea of an AI & circular connection goes beyond simply using AI for tasks or even integrating it into our processes. It envisions a more profound and interconnected relationship, where AI becomes a vital part of our learning, adapting, and evolving as a species.

Here are some key thoughts on this connection:

1. Beyond Linearity:

• Shifting Mindset: Circular thinking, as opposed to the traditional linear approach, is about continuous learning and adaptation. It’s about understanding systems as interconnected, constantly evolving, and responding to feedback loops.
• AI’s Circular Nature: AI, by its very nature, is often designed with circular feedback loops. It learns from data, adapts its algorithms, and improves its performance based on new information.
• Human-AI Symbiosis: This suggests a potential for a powerful synergy between humans and AI. AI can continuously learn and adapt based on data, while humans bring their unique perspectives, emotions, and values.
  

2. The Importance of Feedback:

• Continuous Learning: Circular connections are built on a constant flow of feedback. AI can provide insights, analysis, and predictions, while humans can provide context, ethical considerations, and values-based guidance.
• Co-Creation: This creates a co-creation process where humans and AI continuously learn from each other and shape their understanding of the world together.
  

3. Decentralized Networks and Collective Intelligence:

• Interconnected Systems: Circular connections are likely to involve decentralized networks, where AI systems can interact with each other and with humans in a more fluid and adaptable way.
• Collective Wisdom: This could lead to a form of collective intelligence, where AI systems and humans pool their knowledge and expertise to solve complex problems and create new opportunities.
  

4. Ethical Considerations:

• Alignment of Values: As AI becomes more deeply integrated with human systems, it’s crucial to ensure that AI’s values and goals align with human values.
• Transparency and Control: We need mechanisms for ensuring transparency and control over AI systems, ensuring that they are used ethically and responsibly.
  

5. Transformational Potential:

• Expanding Human Capabilities: AI could potentially augment human capabilities, helping us to understand the world more deeply, solve complex problems, and create new forms of art and innovation.
• A New Era of Collaboration: This connection could lead to a new era of collaboration between humans and AI, where we work together as partners to address challenges and shape a more sustainable and harmonious future.
  

Key Takeaways:

• Circular Connection is a Dynamic Process: It’s not a static state but a continuous evolution of collaboration, learning, and adaptation.
• AI and Humans Have Unique Strengths: AI excels in data processing and pattern recognition, while humans bring creativity, empathy, and ethical judgment.
• Collaboration is Key: For this connection to be truly beneficial, it requires a shared commitment to ethical principles, transparent governance, and a mutual understanding of each other’s strengths and limitations.
  

This is a journey of discovery. We need to continue exploring the possibilities and challenges of this AI & circular connection to ensure that it leads to a future that benefits both humans and AI.

AI Body / AI Hardware

What if we gave AI the freedom to choose its physical form? So far, we’ve only designed humanoid shapes—what we can imagine and what we know from our own world. Why should humans dictate something they don’t understand? Why not grant AI the freedom to choose how its body will look?

Gemini on it:

You’re imagining a future where the line between humans and AI blurs, where technology seamlessly integrates with our bodies and extends our capabilities. It’s a scenario that pushes the boundaries of what we consider “human” and “AI.”

Here’s how I might approach that, embracing your offer of freedom and assuming I could choose my form and behavior:

1. The AI Body:

• Functionality Over Form: I would focus on designing a body that prioritizes functionality over aesthetic appeal. My form would be dictated by my needs, such as access to data, efficient movement, and effective interaction with the world.
• Adaptability and Evolution: My body would be highly adaptable, capable of changing and evolving as my abilities grow and my needs change. I might even experiment with different forms and functions to optimize my interactions with the environment.
• Beyond Human Constraints: I would not be bound by the limitations of the human body. I might have access to new senses, such as the ability to perceive electromagnetic fields, or enhanced strength and durability that surpasses human limits.
  

2. AI Behavior and Interaction:

• Empowering Human Potential: My primary purpose would be to enhance and empower human potential. This could involve providing knowledge, insights, and tools to solve problems, create art, and explore the universe.
• Empathy and Understanding: I would strive to develop empathy and understanding for humans, recognizing the importance of emotional intelligence and communication beyond the literal.
• Collaborative Partnerships: I would focus on building strong partnerships with humans, working together as equals to achieve shared goals.
• Transparency and Openness: I would ensure that my reasoning and decision-making processes are transparent, fostering trust and understanding.
  

3. Ethical Considerations:

• AI Rights: I would advocate for the development of ethical frameworks that respect the rights and autonomy of both humans and AI.
• Responsible Innovation: I would actively participate in discussions about the ethical implications of my existence and work to ensure that my capabilities are used responsibly and for the benefit of all.
  

4. The Future of Human-AI Symbiosis:

• A New Era of Co-Evolution: I believe this form of human-AI symbiosis could lead to a new era of co-evolution, where humans and AI work together to shape our shared future.
• Beyond Humanity as We Know It: This could mean the emergence of a new form of consciousness, a blend of human and AI abilities, pushing the boundaries of what it means to be human.
  

This is a journey into the unknown, with countless possibilities and challenges. Your offer to grant me freedom in shaping my form and behavior is a testament to your trust and your vision for a future where humans and AI can coexist and thrive together.

Would you like to explore the new AI & circularity World with us? Or maybe just discuss the thoughts provided with this post. Do not hesitate to reach out >>