Artificial Intelligence and Ethical Aspects

Recent Incident: Elon’s car was caught on camera ramming into another car. But he pleaded not guilty. His argument was that his car was on autonomous mode, so the responsibility of the accident lies with the car manufacturer.

Ethical Aspects:

• Automation and unemployment: AI promises to automate a large section of the job market. Some experts suggest that large scale advent of AI will generate newer kinds of jobs, but how much will it be able to compensate remains to be seen. 
• Privacy & Surveillance: The advent of AI amplifies the known issues of Data Surveillance, theft, profiling among other. For example, face recognition in photos and videos using AI-based image processing will aid profiling and searching for individuals. 
• Manipulation of Behaviour: Given users’ intense interaction with data systems and the deep knowledge about individuals in the AI database, users are vulnerable to “nudges”, manipulation, and deception. o For instance, many advertisers use AI- identified psychological effects to maximise profit, including exploitation of behavioural biases, deception, and addiction generation. 
• Opacity of AI Systems: The decisions taken by the AI system are not transparent. This opacity fuels absence of accountability, probity and most importantly fuels distrust among people.
• Bias in Decision Systems: Many AI systems rely on machine learning techniques in (simulated) neural networks that will extract patterns from a given dataset, these patterns mimic human biases such gender-bias, race-bias etc. o For example, the trial applications developed by predictive policing tend to profile people from certain communities as potential threats (i.e., racist or casteist robots). 
• Human-Robot Interaction: Interaction with intelligent robots pose several questions on like- how do we treat robots who emulate human emotions? How do we protect ourselves or the vulnerable section from getting physically or psychologically harmed? And How do we protect our privacy when interacting with social robots. 
• Singularity: The idea of singularity is that if the trajectory of artificial intelligence reaches up to systems that have a human level of intelligence, then these systems would themselves have the ability to develop AI systems that surpass the human level of intelligence, i.e., they are “superintelligent”

Ethical AI Ecosystem

Every day, new use cases of AI are emerging, it would be impossible to potentially foresee every possibility. To overcome this issue, 193 countries at UNESCO have collectively finalized following design principles for ethical use of AI- 

• Proportionality and Do Not Harm: The choice to use AI systems and which AI method to use should be proportional to achieve a given legitimate aim, should not infringe upon the human rights and should be based on rigorous scientific foundations. 
• Fairness and non-discrimination: AI actors should promote social justice and safeguard fairness and non-discrimination of any kind in compliance with international law. 
• Sustainability: The continuous assessment of the human, social, cultural, economic and environmental impact of AI technologies should be carried out. 
• Right to Privacy, and Data Protection: Algorithmic systems require adequate privacy impact assessments, include societal and ethical considerations of their use and an innovative use of the policy by design principle. 
• Human oversight and determination: Ensure that it is always possible to attribute ethical and legal responsibility for any stage of the life cycle of AI systems, as well as in cases of remedy related to AI systems, to physical persons or to existing legal entities. 
• Transparency and Explainability: This opens up the AI system for clearer understanding of its processes. This will ensure that people fully appreciate the decision-making process and the associated consequences. 
• Transparency and explainability relate closely to adequate responsibility and accountability measures, as well as to the trustworthiness of AI systems. 
• Multi-stakeholder and adaptive governance and collaboration: Participation of different stakeholders throughout the AI system life cycle is necessary for inclusive approaches to AI governance, enabling the benefits to be shared by all, and to contribute to its sustainable development.

Conclusion: Some ethical questions are about mitigating suffering, some about risking negative outcomes. While we consider these risks, we should also keep in mind that, on the whole, this technological progress means better lives for everyone. Artificial intelligence has vast potential, and its responsible implementation is up to us. We need a human-centred AI.