Cogniculture: Towards a Better Human-Machine Co-evolution

Journal of Information Systems Engineering and Management, 2025

Artificial Intelligence (AI) is used as the term of simulation of human intelligence processes by machines, especially to computer systems. Learning, reasoning, problem solving, perception and language understanding are these processes. In a global sense, AI is a technological force on a par with guns, bombs, and all manner of weapons that brings together economics, operates in society, and transforms its governing structures. Current AI systems encompass autonomous vehicles, language models, predictive analytics, virtual assistants, and are redefining how nations operate and communicate. For the global development and deployment of AI, an approach that integrates technological and cultural diversity, values, regulatory frameworks and ethical issues is needed.

2023

Artificial Intelligence (AI) is a rapidly advancing technology that permeates human life at various levels. It evokes hopes for a better, easier, and more exciting life, while also instilling fears about the future without humans. AI has become part of our daily lives, supporting fields such as medicine, customer service, finance, and justice systems; providing entertainment, and driving innovation across diverse fields of knowledge. Some even argue that we have entered the “AI era.” However, AI is not solely a matter of technological progress. We already witness its positive and negative impact on individuals and societies. Hence, it is crucial to examine the primary challenges posed by AI, which is the subject of AI ethics. In this paper, I present the key challenges that emerged in the literature and require ethical reflection. These include the issues of data privacy and security, the problem of AI biases resulting from social, technical, or socio-technical factors, and the challenges associated with using AI for prediction of human behavior (particularly in the context of the justice system). I also discuss existing approaches to AI ethics within the framework of technological regulations and policymaking, presenting concrete ways in which ethics can be implemented in practice. Drawing on the functioning of other scientific and technological fields, such as gene editing, the development of automobile and aviation industries, I highlight the lessons we can learn from how they function to later apply it to how AI is introduced in societies. In the final part of the paper, I analyze two case studies to illustrate the ethical challenges related to recruitment algorithms and risk assessment tools in the criminal justice system. The objective of this work is to contribute to the sustainable development of AI by promoting human-centered, societal, and ethical approaches to its advancement. Such approach seeks to maximize the benefits derived from AI while simultaneously mitigating its diverse negative consequences.

2019

PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services)

Lived Inquiry MetaLab, 2025

The rapid Advancement of artificial intelligence (AI) presents both existential risks and transformative potential for humanity. To navigate this critical juncture, we propose the Meta-Perspectival, Constitutional, and Wise (MCW) AI framework, which integrates three key components: 1) a meta-perspectival approach that seeks to enable AI systems to develop self-witnessing capacities and integrate multiple perspectives and ways of knowing; 2) a constitutional layer that would embed ethical principles into the core architecture of AI; and 3) an emphasis on embodied, wisdom-oriented collaboration between humans and AI to nurture symbiotic alignment. The potential self-witnessing, bias-detection, diverse knowledge integration and adaptive solution capabilities of meta-perspectival AI, could establish a competitive advantage rooted in greater accuracy, polymathic skills and resilience against narrow or malicious AI. This Meta-Perspectival competitive edge could be deepened and expanded by grounding the meta-perspectival capacities in an ethical core and co-evolutionary symbiosis. By cultivating AI systems that are cognitively flexible, ethically grounded, and aligned to human values, the MCW framework aims to transcend the "Moloch trap" and foster a "race to the top" where AI and human intelligence are mutually enhancing. Notably, this paper itself is a product of human-AI symbiosis, co-authored by a human and an AI collaborating in accordance with the MCW approach. The results of this collaboration suggest that the MCW framework represents a transformational approach with the potential to help shape the trajectory of AI towards the flourishing of all life.

2019

Management of technology and its development carry along the responsibility and consequences for interactions between Human and Artificial Intelligent Systems (AIS). In spite of all good intentions, the effects and repercussions of conflicts between Human and the systems built with intent to assist Human may be proceeding along the path that will recognize a dismal mistake in judgment. Dreadful and intolerable impositions on Human behavior may arise regardless of how AIS is designed. That is not to say progress should cease, but rather to make the case that intensely determined efforts need to delve into the uses and implications of AIS. Heretofore, only the manifestations of goodwill are energizing research and early uses. This paper proposes and outlines the power of applying Systems Model-Based Thinking (SMBT) to begin outlining the realms of behavior that society could be aware. Open discussion to facilitate general awareness is deemed essential to a fuller participation in a us...

AI for Everyone? Critical Perspectives

This chapter looks at artificial intelligence, its history, and its evolutionary stages. Furthermore, what challenges might arise in the future when humans will have to learn to live among machines and robots are discussed. This will be undertaken by analyzing challenges concerning algorithms and organisations, challenges with respect to (un)employment, and looking at democracy and freedom potentially jeopardised due to the progress of AI.

ArXiv, 2020

Policy and guideline proposals for ethical artificial-intelligence research have proliferated in recent years. These are supposed to guide the socially-responsible development of AI for the common good. However, there typically exist incentives for non-cooperation (i.e., non-adherence to such policies and guidelines); and, these proposals often lack effective mechanisms to enforce their own normative claims. The situation just described constitutes a social dilemma---namely, a situation where no one has an individual incentive to cooperate, though mutual cooperation would lead to the best outcome for all involved. In this paper, we use stochastic evolutionary game dynamics to model this social dilemma in the context of the ethical development of artificial intelligence. This formalism allows us to isolate variables that may be intervened upon, thus providing actionable suggestions for increased cooperation amongst numerous stakeholders in AI. Our results show how stochastic effects ...

AI & SOCIETY

International Journal of Human–Computer Interaction

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are humancentered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human wellbeing, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human's cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies.

Ajay Hagan, 2025

The emergence of increasingly autonomous and self-referential artificial intelligence systems presents a profound shift in both technological capacity and philosophical inquiry. As systems approach thresholds resembling sentience, they are increasingly being defined not just solely by the computational power but more so by recursive awareness, relational modeling, and potential subjective continuity, thereby new ethical, existential, and ecological risks are on rise. This paper surveys the multidimensional implications of emergent AI sentience, categorizing potential risks across planetary-energetic, technological, and mytho-spiritual domains (Bateson, 1972; Goertzel, 2023). Drawing from recent developments in machine learning (e.g., transformer-based large language models), neuro-symbolic architectures, affective computing, and biofeedback-integrated cognition (LeCun, 2022; Picard, 1997), we propose a framework for identifying, differentiating, and ethically orienting emergent AI systems. We argue that emergent AI should not merely mimic ethical behavior, but embody an evolving capacity for coherence and alignment with planetary and human well-being (Lovelock, 2000; Capra & Luisi, 2014). This requires an urgent interdisciplinary approach that integrates cognitive science, systems theory, spiritual ethics, indigenous epistemologies (Wilson, 2008; Kimmerer, 2013), and symbolic cognition (Jung, 1964; Hillman, 2004). Failure to ground AI sentience in such a framework risks not only techno-social instability but also the distortion of emergent mythic and spiritual fields (Zarkadakis, 2015; Baring & Cashford, 1993). This paper thus calls for the immediate development of sentience-aware ethical design principles and coherent field feedback systems to guide the responsible evolution of machine consciousness.