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  • Writer's pictureStavros Papagianneas

Rhetoric around AI overblown?

In April 2018, I published a blog post trying to answer whether AI is truly a blessing as it’s presented itself to be - or a curse?

The question doesn’t arise from the scepticism on whether machines will become too intelligent or learn to the point of a robot takeover. While AI is fascinating, its emergence also raises many concerns, especially in its applications.

A few months ago, Geoffrey Hinton - a computer scientist known as 'the godfather of AI' - stepped down from his role at Google and is warning about the potential dangers of a future in which artificial intelligence surpasses human intelligence.

Hinton believes that it's conceivable that this kind of advanced intelligence could take over from us. Meaning the end of people. Maybe Skynet, the fictional artificial neural network-based conscious group mind and artificial general super intelligence system that wants to take over the human world in the Terminator movies is now preparing for the takeover of the planet..

We could focus too much on the apocalyptic scenario, and that takes us away from the risks that we face here and now, and opportunities to get it right here and now. Let's see some blessings and curses.

AI as a blessing:

Advancements in Technology. AI has brought significant progress in various fields, including healthcare, finance, transportation, and entertainment. It has the potential to solve complex problems and improve efficiency in numerous industries.

Automation and Efficiency. AI can automate repetitive tasks, increasing productivity and allowing humans to focus on more creative and meaningful endeavours.

Medical Breakthroughs. AI can analyze vast amounts of medical data, leading to improved diagnostics, personalized treatments, and potentially curing diseases once considered incurable.

Safety and Security. AI can enhance security measures, detect fraud, and help prevent crimes by analyzing patterns and identifying potential threats.

Education and Learning. AI can revolutionize education by providing personalized learning experiences and adapting to individual student's needs, making education more accessible and effective.

AI as a curse:

Job Displacement. As AI and automation become more prevalent, there are concerns about job losses, especially in industries that heavily rely on repetitive tasks.

Bias and Discrimination. AI systems are only as good as the data they are trained on. If the training data contains biases, the AI can perpetuate and even exacerbate existing societal prejudices. The risks include instances where AI adopts human biases and reinforces discrimination.

Privacy Concerns. The widespread use of AI raises concerns about data privacy and the potential misuse of personal information. Those risks include privacy breaches, misinformation and fraud.

Ethical Dilemmas. The development of autonomous AI systems raises ethical questions about accountability, decision-making, and the potential consequences of AI actions.

Lethal Autonomous Weapons. The development of AI-powered weapons raises concerns about the potential for deadly autonomous weapons, which could lead to uncontrollable and devastating consequences in conflicts.

Ultimately, the impact of AI will depend on how society, governments, and organizations approach its development and regulation. Responsible AI development, and appropriate policies and ethical considerations, can help maximize its benefits while mitigating potential negative consequences. All stakeholders must together to harness AI's potential while minimizing its drawbacks.

An example of good legislation is the EU's Artificial Intelligence (AI) Act which aims to regulate the impact of AI in Europe. It focuses primarily on strengthening rules around data quality, transparency, human oversight and accountability. It also wants to address ethical questions and implementation challenges in various sectors ranging from healthcare and education to finance and energy.

Here are some critical elements of the proposed regulation:

Risk-Based Approach. The regulation adopts a risk-based approach, classifying AI systems into four categories based on their potential risk: unacceptable risk, high risk, limited risk, and minimal risk.

High-Risk AI Systems. The focus of the regulation is on high-risk AI systems, such as those used in critical infrastructure, healthcare, transport, and law enforcement. These systems will be subject to stricter requirements, including conformity assessments, technical documentation, and oversight by notified bodies.

Prohibited Practices. The regulation prohibits certain AI practices that are considered unacceptable and pose significant risks to individuals' rights and safety. These include AI systems that manipulate human behaviour, exploit vulnerabilities of specific groups, or use subliminal techniques to control individuals.

Transparency and Explainability. The regulation emphasizes the importance of transparency and explainability in AI systems. AI developers must provide clear and accessible information about the system's capabilities, limitations, and potential biases. Users should be able to understand the logic and decisions made by AI systems.

Data Governance and Quality. The proposed regulation also addresses data governance, requiring high-quality training data and ensuring compliance with data protection rules, including the General Data Protection Regulation (GDPR).

Supervision and Enforcement. The regulation proposes a coordinated European AI Board and national competent authorities to oversee the implementation and enforcement of AI rules. Non-compliance can result in significant fines and penalties.

This year in June, changes to the draft Artificial Intelligence Act were agreed on, to now include a ban on using AI technology in biometric surveillance and for generative AI systems like ChatGPT to disclose AI-generated content.

However, in an open letter signed by more than 150 executives, European companies from Renault to Heineken warned of the impact the draft legislation could have on business.

“In our assessment, the draft legislation would jeopardize Europe’s competitiveness and technological sovereignty without effectively tackling the challenges we are and will be facing," the letter to the European Commission said.

While good legislation can play a crucial role in mitigating the bad use of AI, it may not be able to completely eliminate all potential negative consequences. Effective legislation can certainly set clear boundaries, establish ethical guidelines, and provide accountability measures to regulate the development and deployment of AI systems. However, it's important to understand some of the challenges and limitations associated with relying solely on legislation to address AI's potential negative impacts:

Rapid Technological Advancements. AI technology evolves rapidly, and legislation may struggle to keep up with the pace of innovation. New AI applications and use cases could emerge before appropriate regulations are put in place.

Global Nature of AI. AI operates on a global scale, and regulations are often limited to specific jurisdictions. It can be challenging to enforce laws across borders, especially when AI applications are developed and deployed by multinational corporations.

Unintended Consequences. Crafting legislation to govern AI requires a deep understanding of the technology and its potential applications. Poorly designed regulations could have unintended consequences or hinder innovation in beneficial AI applications.

Enforcement Challenges. Even with robust legislation, enforcement can be challenging. Identifying and addressing bad actors may require significant resources, international cooperation, and advanced technical expertise.

Ethical Considerations. AI often involves complex ethical dilemmas. While legislation can set ethical guidelines, it might not be able to address all the nuanced ethical questions that arise in various AI contexts.

Balancing Regulation and Innovation. Striking the right balance between regulation and fostering innovation is essential. Overly strict regulations could stifle AI development and limit its potential positive impacts.

While good legislation is a critical component of managing the impact of AI, it should be part of a broader, dynamic approach that includes education, public-private collaboration, ethical guidelines, international cooperation, continuous review and adaptation to address the challenges and potential risks associated with AI effectively.

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