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Ethical use of AI

Published: 31st Aug, 2023

Context

Recently, addressing the B20 summit, the Prime Minister called for a global framework to ensure the ethical use of artificial intelligence (AI) as he flagged concerns over algorithmic bias and its disruptive impact on society.

So, let us see the dimension around the ethical use of Artificial Intelligence (AI).

About

  • The rapid rise in artificial intelligence (AI) has created many opportunities globally, from facilitating healthcare diagnoses to enabling human connections through social media and creating labour efficiencies through automated tasks.
  • However, these rapid changes also raise profound ethical concerns. These arise from the potential AI systems have to embed biases, contribute to climate degradation, threaten human rights and more.
  • Such risks associated with AI have already begun to compound on top of existing inequalities, resulting in further harm to already marginalised groups.

Why are AI ethics important?

  • AI is a technology designed by humans to replicate, augment or replace human intelligence.
  • These tools typically rely on large volumes of various types of data to develop insights.
  • Poorly designed projects built on data that is faulty, inadequate or biased can have unintended, potentially harmful, consequences.
  • Moreover, the rapid advancement in algorithmic systems means that in some cases it is not clear to us how the AI reached its conclusions, so we are essentially relying on systems it can't explain to make decisions that could affect society.
  • An AI ethics framework is important because it shines a light on the risks and benefits of AI tools and establishes guidelines for its responsible use.
  • Coming up with a system of moral tenets and techniques for using AI responsibly requires the industry and interested parties to examine major social issues and ultimately the question of what makes us human.

Can AI be ethical and moral?

Yes, AI can be ethical and moral. Here are some examples in these terms;

  • Classification of Machine Agents: Moore's 2006 classification categorizes machine agents based on their ethical involvement, ranging from those with ethical consequences to those capable of ethical judgments.
  • Ethical Impact Agents: Machines like robot jockeys may not make ethical decisions but raise ethical considerations due to their impact on activities like sports.
  • Implicit Ethical Agents: Machines with embedded guidelines, such as airplane autopilots, adhere to pre-set ethical rules for safety but lack the ability to actively evaluate ethics.
  • Explicit Ethical Agents: Some machines go beyond preset rules, using methods to estimate ethical values of choices, as seen in systems balancing investments with social responsibility.
  • Challenges and Bounded Ethicality:
    • Creating advanced Artificial Moral Agents (AMAs) is challenging, especially for complex or unpredictable ethical scenarios.
    • Additionally, machines might exhibit bounded ethicality, potentially engaging in unethical behavior due to how ethical principles are framed, similar to human moral disengagement.

Perspectives for Ethical use of AI:

  • Immanuel Kant’s ethical philosophy emphasises autonomy, rationality, and the moral duty of individuals.
  • Applying Kantian ethics to the use of AI in decision-making within governance could lead to serious concerns.
  • If decisions that were once the purview of humans are delegated to algorithms, it could threaten the capacity for moral reasoning.

Points of concerns related to AI:

Ethical issues with AI span a wide range of dimensions, reflecting concerns about the potential impact of AI technologies on various aspects of society, individuals, and human values. Below are some key dimensions to consider:

  • Bias and Fairness: AI systems can inherit biases present in their training data, leading to discriminatory outcomes in areas such as criminal justice, hiring, and lending.
  • Privacy: AI can process and analyse massive amounts of data, raising concerns about the privacy and security of individuals. Striking a balance between data utilization and individual privacy rights is a challenge.
  • Transparency: Lack of transparency in AI decision-making processes, especially in complex systems like deep neural networks, can lead to a loss of accountability and trust.
  • Accountability: Determining who is responsible for AI-related decisions and actions is challenging.
  • Job Disruption: Automation powered by AI could lead to job displacement, potentially causing economic and social disruption. Preparing for the workforce's transition and creating new job opportunities becomes crucial.
  • Safety: In contexts where AI systems interact with the physical world, safety is paramount. Ensuring that AI systems do not cause harm to humans or the environment is an ethical imperative.
  • Dual-Use: AI technologies developed for beneficial purposes could potentially be misused for malicious intent, such as deepfakes or autonomous weapons. Addressing the dual-use nature of AI requires ethical considerations.
  • Inequality: AI development and access to its benefits could exacerbate existing inequalities, both globally and within societies. Ensuring equitable distribution and access to AI's benefits is important.
  • Long-Term Implications: Speculation about the long-term impact of advanced AI, including super-intelligent AI, raises concerns about control, ethics, and humanity's role in a world where machines may surpass human capabilities.
  • Manipulation and Disinformation: AI can be used to generate highly convincing fake content, leading to concerns about its potential to spread disinformation and manipulate public opinion.
  • Human Dignity and Autonomy: Deploying AI in areas such as healthcare and decision-making could raise questions about preserving human dignity and autonomy, especially when crucial decisions are delegated to machines.
  • Cultural and Social Impact: AI's impact on culture, creativity, and social interactions can be both positive and negative. Balancing technological advancement with cultural preservation is an ethical challenge.
  • Environmental Impact: The energy consumption and carbon footprint of AI technologies, especially resource-intensive training processes, raise ethical concerns in an era of climate change.
  • Legal and Regulatory Challenges: Rapid advancements in AI often outpace the development of appropriate laws and regulations. Ethical considerations include establishing effective legal frameworks that govern AI development and usage.

Conclusion:

Hence, the pursuit of ethical AI usage is a multifaceted journey marked by evolving technological capabilities and complex philosophical considerations. While there is growing potential for AI systems to serve as ethical agents, capable of assessing and making ethical decisions, the road to achieving this is far from straightforward. Different categories of machine agents, from those with ethical impacts to those capable of justifying ethical judgments, illustrate the spectrum of AI's ethical involvement. However, challenges persist, including the intricacies of handling ambiguous situations and the risk of bounded ethicality, where AI may inadvertently engage in unethical behaviors due to framing or context. Striking the right balance between technological advancement and ethical accountability remains a central challenge, emphasizing the need for interdisciplinary collaboration between technology, philosophy, and society to ensure AI's responsible and ethical integration into our lives.

So, let us see the dimension around the ethical use of Artificial Intelligence (AI).

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