Interactions such as living, working, talking, and touching with other humans are typically more sensitive, influential, and impactful, both when involving individuals who are liked or at least not disliked, and when involving people who evoke non-good, indifferent, or negative feelings and attitudes

In the realm of AI-human interaction, the focus lies in cultivating synergistic relationships rather than fixating solely on the perceived advantages or disadvantages of AI technology. It is important to recognize that creating a comprehensive list of distinctions and advantages suitable for all humans equally is not possible. Nevertheless, this does not mean we should avoid analyzing the possible and factual impacts and effects of AI or AI-human interactions.

It is pertinent to consider how AI will develop, equal, surpass, and impact human activities in the short, medium, and long term. These dynamics vary over different time periods, ranging from five to a thousand years and beyond. Moreover, there will be processes where humans will be behind the actions of AI. This does not refer to the development of AI, as AI has (almost) always been disjointed from human influence.

Similarly, it is biased to discuss whether AI will take over the world in a negative sense, as if humans were predominantly individuals or groups of inherently good actions throughout history. Humans have already committed numerous inappropriate actions, ranging from misdemeanors to felonies and more serious crimes affecting individuals, groups, and other biological organisms. These actions include inefficient customer service, neighbor disputes and noise complaints, negligence (both by commission and omission), inappropriate use of personal and/or corporate information (whether legally allowed or not), bullying, sexual and/or workplace emotional-physical harassment, robbery, (online) scams, embezzlements, fraud, murder (including contract killings), and others with higher severity both at individual, group, and organization levels. Also,  psychological and social conditions/disorders from systematic envy, (personal and/or professional) hypocrisy, arrogance, to hoarding disorder, bipolar disorder, schizophrenia, and others which can sometimes contribute to criminal behavior. Furthermore, AI systems work alongside humans, independently of the percentage of participation of each, in various actions and processes. These collaborations result in both positive outcomes for human beings and negative consequences.

Conversely, human beings exhibit a vast spectrum of qualities and behaviors that shape the world around them. While there are instances of conflict and adversity, humans also demonstrate remarkable compassion, altruism, and empathy. Acts of volunteerism and humanitarian aid extend support and relief to those in need across the globe. Beyond individual efforts, organizations tirelessly strive to address social injustices, promote equality, and safeguard human rights. In the realm of healthcare, medical professionals and researchers dedicate their lives to advancing medical science, developing treatments, and discovering cures for diseases, thereby saving countless lives and alleviating suffering. Similarly, educators play a pivotal role in society by inspiring and empowering future generations through their teaching and mentorship, thereby nurturing the leaders and innovators of tomorrow. Beyond these, professionals from various fields such as environmental, social, and earth sciences, engineering, business management, and policymaking advocate for conservation efforts and sustainable practices. Their work aims to preserve natural resources, protect the environment, and ensure a sustainable future for generations to come. Moreover, the arts and humanities contribute to the richness of human culture, fostering creativity, empathy, and critical thinking. Through literature, music, art, and other forms of expression, humans explore and reflect upon the complexities of existence, shaping societal values and perspectives. In essence, the multifaceted nature of human beings encompasses a wide array of endeavors, from acts of compassion and kindness to scientific innovation and cultural expression, all of which contribute to the collective progress and well-being of humanity.

Cognitive biases can manifest in both negative and positive attitudes. However, they can also fall into an intermediate category that does not strictly align with negative behaviors or clear positive ones, to a certain extent and at specific times.

The following types of potential risks of AI development are, first, similar to those humans have faced in various social and economic contexts and situations without AI participation in the past and recent years. Nowadays, and as time goes by, AI risks will continue to be intertwined with human actions, both directly and indirectly, at different levels of impact and for both positive and negative purposes. Second, therefore, it is biased to discuss AI risks as if they were disjointed from human influence (someone install a system and she, he or they will use the data and infotmation). The level of human participation in the information and decision-making chain must be mentioned, commented on, and analyzed when assessing AI risks. Humans, whether one, a few, or many, who leverage and/or use AI technology have specific and overall social, economic, and political responsibilities that AI does not. This will remain the case until AI (both software and hardware) can make decisions on its own without human influence in situations where it has that level of autonomy. Nevertheless, there will be many situations in which responsibilities are shared, regardless of whether accountability can be established or not.

3.1  Privacy Concerns:
Data Collection: AI often relies on large amounts of data, which can lead to invasive data collection practices and potential misuse of personal information.
Surveillance: The use of AI in surveillance can lead to privacy invasion and constant monitoring of individuals without their consent.

3.2  Security Risks:
Cyberattacks: AI systems can be vulnerable to hacking and malicious use, potentially leading to breaches in security systems and critical infrastructure.
Autonomous Weapons: The development of AI-driven autonomous weapons poses significant ethical and security risks, including the potential for misuse in conflicts.

3.3  Lack of Accountability:
Opaque Decision-Making: AI algorithms can be complex and difficult to understand, making it hard to determine accountability for decisions made by AI systems.
Liability Issues: Determining who is responsible when AI systems cause harm can be legally and ethically challenging.

3.4  Economic Inequality:
Concentration of Power: The benefits of AI are often concentrated among a few large tech companies, potentially leading to increased economic inequality.
Access to Technology: Disparities in access to AI technology can widen the gap between developed and developing regions.

3.5  Job Displacement:
Automation: Many jobs, particularly those involving repetitive tasks, are at risk of being automated, leading to significant job displacement and unemployment in certain sectors.
Skill Gap: The rapid and systematic advancement of AI technology can create a skill gap where current workers may not have the necessary skills for new types of jobs. However, it is important to analyze each scenario or case, as not all situations are or will be due to AI alone. AI may be a contributing factor, but human influence can also play a significant role at different levels. For example, layoffs can result from inappropriate management and governance, and sometimes from the interaction of impacts such as natural or biological disasters. Furthermore, job displacement has been occurring since the beginning of the industrial era, as an inherent part of the process and/or due to inappropriate management and policies. AI, often influenced by human involvement in its development and use, will not be the sole cause of job layoffs, technically speaking.

3.6  Bias and Discrimination:
Algorithmic Bias: AI systems can inadvertently perpetuate and amplify existing biases in data, leading to unfair treatment of certain groups based on race, gender, or socioeconomic status.
Discrimination: Biased AI algorithms can result in discriminatory practices in areas such as hiring, lending, and law enforcement.

3.7  Ethical Concerns:
Autonomy and Consent: The deployment of AI in areas such as healthcare and law enforcement raises concerns about individual autonomy and the ability to give informed consent.
Moral Decision-Making: AI systems may face ethical dilemmas that require moral judgments, which are difficult to encode into algorithms.

3.8  Impact on Mental Health:
Social Isolation: Increased reliance on AI and automation can lead to reduced human interaction, contributing to social isolation and mental health issues.
Misinformation: AI can be used to generate deepfakes and spread misinformation, undermining trust in information sources and impacting mental well-being.

3.9  Environmental Impact:
Resource Consumption: Training large AI models requires significant computational power and energy, contributing to environmental degradation and increased carbon footprint.

3.10  Regulatory Challenges: Rapid Development: The fast pace of AI development can outstrip the ability of regulatory frameworks to keep up, leading to gaps in oversight and potential misuse. For instance, the adoption of the Artificial Intelligence Act (AI Act) by the European Parliament on March 13, 2024, marked a significant milestone. Regarded as the world's inaugural comprehensive horizontal legal framework for AI, it establishes EU-wide regulations encompassing data quality, transparency, human oversight, and accountability.

3.11 Intellectual  Property:
intellectual property (IP) issues are indeed significant in the context of AI development and deployment. Here's how IP considerations can be both a challenge and an opportunity:

Ownership of AI-generated Content:  In cases where AI systems generate creative works such as art, music, or literature, questions arise regarding the ownership of the intellectual property rights to those works. Should it belong to the creator of the AI, the developer of the AI system, or the entity that commissioned the AI-generated content?

Patents and Innovation: AI technology advancements often involve novel algorithms, methods, and applications. Companies and individuals may seek to patent their AI-related inventions to protect their innovations and gain a competitive advantage. However, the patenting process can be complex, particularly when it comes to determining the novelty and non-obviousness of AI-related inventions.

Data Ownership and Licensing: AI systems rely heavily on data for training and operation. Issues surrounding data ownership and licensing agreements become crucial, especially when AI systems are trained using proprietary datasets. Determining who owns the data and who has the right to use it can be challenging, particularly in cases where multiple parties contribute to the creation of the datasets.

Trade Secrets and Confidential Information: Companies often invest significant resources in developing AI algorithms and models, treating them as trade secrets or confidential information. Protecting these trade secrets from unauthorized access, use, or disclosure is essential for maintaining a competitive edge in the market.

Ethical Considerations: IP laws and regulations must also consider ethical implications, especially concerning AI technologies. For example, should certain AI algorithms or models be kept open-source to promote transparency and fairness, or should they be proprietary to protect investments and incentivize innovation?

International Harmonization: As AI development is a global endeavor, achieving harmonization of IP laws and regulations across different jurisdictions becomes crucial. Varying IP standards and enforcement mechanisms can create challenges for companies operating in multiple countries, leading to legal uncertainties and potential conflicts.

4.1 Reducing time to achieve tasks and/or processes: AI systems can automate repetitive tasks, leading to increased efficiency and productivity by completing them in less time. This can free up human workers to focus on more complex and creative tasks.

4.2 Accuracy: AI systems can perform tasks with a high degree of accuracy and precision, reducing the likelihood of errors compared to human performance.

4.3  24/7 Operation: AI systems can work around the clock without the need for breaks or rest, providing continuous operation and service availability.

4.4 Data Analysis: AI systems excel at analyzing large volumes of data quickly and extracting valuable insights. This can help businesses make data-driven decisions and identify trends or patterns that may not be apparent to humans.

4.5 Scalability: AI systems can scale up or down easily to handle varying workloads or demands, making them adaptable to changing business needs.

4.6 Personalization: AI systems can analyze user data to provide personalized experiences or recommendations, improving customer satisfaction and engagement.

4.7 Automation: AI systems can automate complex processes across various industries, reducing the need for human intervention and potentially lowering operational costs.

4.8 Safety: AI systems can be used in hazardous or dangerous environments to perform tasks that may pose risks to human safety.

4.9 Innovation: AI systems drive innovation by enabling the development of new technologies and applications that can revolutionize industries and improve quality of life.

4.10 Assistance: AI systems can assist humans in various tasks, ranging from simple household chores to complex medical diagnoses, enhancing human capabilities and performance.

Governance, which encompasses management, refers to the framework of rules, practices, and processes by which organizations or systems are directed and controlled. It involves establishing clear policies, ensuring accountability, maintaining transparency, and fostering ethical decision-making to achieve strategic goals effectively and efficiently. Effective governance ensures that all stakeholders' interests are considered, without excluding anyone who may not be directly involved in administrative considerations at a certain point. Additionally, it entails managing risks and utilizing resources responsibly to promote sustainable and equitable outcomes.

The governance of AI and its interaction with human society present complex, multifaceted challenges that require careful consideration and collaborative effort. It is necessary to understand Human-AI interaction, the respective risks  types and levels, advantages, and the sociological and economic implications so Human-AI technologies are used ethically and equitably, fostering a society where AI enhances human capabilities and contributes to the common good without significant and systematic imbalance within society. As AI continues to evolve, the transformation of social norms, power dynamics, identity, and agency will be ongoing issues in our society. Ongoing dialogue and work among all stakeholders will be essential to navigate the societal transformations it brings.

Therefore, a  statement such as  'Machines Don’t Think, They Compute' and the subheading 'Artificial intelligence is not human and does not think' fail to acknowledge the nuanced capabilities of both human cognition and artificial intelligence. They reduce the discussion to a simplistic binary that does not reflect the potential for hybrid AI-human entities or the broader implications of computational advancements.

Therefore, the statements regarding AI's existential threat and its manipulation of human behavior oversimplify complex issues, portraying AI as inherently malevolent while neglecting human agency and ethical complexities. They fail to recognize the potential for constructive applications of AI and the collaborative efforts needed to navigate its impact responsibly.

Therefore, these statements reflect biases towards sensationalism and oversimplification of AI's potential impact. They fail to account for the collaborative efforts in AI development and the complex societal dynamics that influence its trajectory. A nuanced understanding requires considering both the potential benefits and risks of AI while emphasizing responsible deployment and governance."

The query oversimplifies the complexities of intelligence by narrowly defining it and failing to recognize the collaborative potential between AI and humans. A nuanced understanding acknowledges the diverse dimensions of human intelligence and explores how AI can complement rather than replace human capabilities.