Artificial Intelligence Multiverse

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introduction

In 2021, Amazon and Google won bids to provide the Israeli government with cloud computing services up to “The Mundane Google Meet Video Chatss to Qualtisticated Machine-Learning Tool.” The contract, known as Project Nimbus, accounted for less than half of Google's revenue in 2021. However, it represents a key strategic move for Google's cloud services division, putting the company in a competitive position with regard to “a large-scale cloud business of Amazon and Microsoft.” The procurement contract is surrounded by the centre of the contributions of private-based digital transformation. However, concerns about using cloud services for more military-based purposes in the West Bank and “promoting human rights violations” risked Google's reputation being damaged.

At the same time, Google's Deepmind team has created a research report titled “AI Helps Humans Find Common Foundations in Democratic Deliberations,” which conveys the findings from Habermas Machine, a large-scale language model (LLM) that acts as AI mediators. Habermas Machine is an AI system built by Google researchers that can “respect the views of the majority of each of our small groups” and by acknowledging the views of minorities can produce an output that “doesn't make the minority feel deeply stripped.” This innovation for conflict resolution is still in its early stages and contains flaws, but it shows how companies exist within the flow to advance technology for peaceful mediation, and at the same time contributes to the perpetuation of violent conflicts in other regions.

The choice of AI companies to pursue commercial interests linked to military applications poses the issue of turning economic behavior into political behavior.

As a result, these companies play multiple roles. Producers of AI innovation, sellers of the infrastructure that AI technology needs to expand its capabilities or software, and collaborators who provide official developers with the tools they need to create mission-critical solutions. To pursue this multiple role simultaneously, tech companies must follow a conflicting set of objectives. It's about making money, pursuing scientific research, meeting market needs, and having innovative ideas. Technology companies face constantly significant internal and external pressures when navigating commercial interests and impacts on society from a conflict and resolution perspective.

How can AI be reconciliated depending on how it can cause conflicts and enable resolution, and how it is used? What sets AI apart from other innovations is its classification as a general purpose technology. AI systems can be widely spread across sectors within these sectors and specific domains for many uses, from public sector policing to fraud detection in the financial sector. Therefore, such systems require unique concepts of governance that cannot be compared to other dual-used technologies such as nuclei. The most widely used and updated definition of artificial intelligence systems is to be a “machine-based system,” which is a “how to generate, for explicit or implicit purposes, output, such as predictions, content, recommendations, or decisions, that can affect a physical or virtual environment, from the input received. Every day, humans experience and interact with varying degrees of AI, including machine learning systems that drive Netflix's film recommendation algorithms. Therefore, user feedback can be adapted in real time.

The controversial nature of private sector involvement in the production of double-use AI means that the culture and structure of an organization must adapt in innovative ways. At the same time, the public sector must answer difficult questions through institutionalization mechanisms to protect, guide, guide and build AI in the public interest.

While some technology companies help incorporate AI into military operations, others are focused on how the technology enhances conflict resolution processes, such as mediation and peacebuilding. Sometimes this happens within the same organization. To effectively link human ownership to AI-based actions, there must first be a clear distinction between military fusion at the organizational level. This makes tasks clearly align to the intended purpose of AI. Second, at the social level, appropriate institutions need to be established that provide a mechanism for placing human responsibility for actions and actions arising from the use of AI to create opportunities for justice, potential responsibilities, and penalties for misuse. At the government level, the complex and multifaceted nature of emerging technologies requires careful consideration of public protection mechanisms. Finally, at the individual level, more coordinated efforts are needed to rethink how current technical and business-oriented models, and the design choices that support them, affect the democratic liberal values ​​that are the basis of democracy.

The views expressed in this article are those of the authors and not the official policy or status of the new Line Institute.