Ethical AI
Responsible AI

Ethical AI

Ethical AI defines guidelines for individual rights, behavior manipulation, privacy, and non-discrimination to ensure legitimate use of AI

What is Ethical AI?

AI ethics is a branch of Digital Ethics that covers ML fairness, privacy and surveillance, non-manipulation, robotic insights, and accountability of autonomous systems.

Ethical AI brings well-defined guidelines for individual rights, behavior manipulation, privacy, and non-discrimination. AI ethics drive considerations on determining legitimate and non-legitimate uses of artificial intelligence. The Ethical AI approach defines guided policies and appropriate review processes to ensure AI ethics in the organization.   

Human beings possess different cognitive biases that consequently exhibit in their behavior and data. Now, this data forms the building block for any ML system. These ML systems get affected by biased data. Ethical AI comes into the picture to build sustainable AI systems that overcome unforeseen consequences of biased datasets and human behavior.

Why Ethical AI Matters?

“Technology is a useful servant but a dangerous master.”

Like any technology, AI also has the potential for good and evil applications. Defining ethical practices for ML initiatives helps ensure that AI benefits people, organizations, and society as a whole. These practices benefits organizations with

  • Enhanced operational efficiency
  • Reduced hazardous environmental impacts
  • Increased public safety
  • Gender and societal equality for different initiatives

However, the lack of an ethical framework can produce unwanted outcomes such as deception, abuse, misinformation, and harmful effects for individuals and society.

Ethical AI exceeds legal framework and regulations to highlight the importance of human values. Legally allowed practices consider set acceptability criteria, whereas ethical practices exceed legal requirements and consider human values.

Ethical AI- A Three-Stage Approach

Implementing ethical AI requires compliance with ethical practices at people, process, and technology levels.

  • At the people level, fostering awareness of ethical AI practices, understanding bias types, and their impact on businesses is essential
  • Process level guidelines include ensuring governance, data, and delivery processes such as fairness measures, identifying advantaged and disadvantaged groups, data sampling to check bias and fairness. Other process-level practices include ensuring end-to-end traceability, flagging bias-related issues, and manual intervention at the right time
  • Technology-based ethical AI practices include the right choice of tool, technology, and adherence to best practices
Components that make up a good ethical AI framework
Components that make up a good ethical AI framework

Ethical AI at Censius

Censius practices and respects ethical AI. We understand the importance of ethical behavior and values. Our commitment to ethical AI reflecting in our practices:

  • Commitment to working in legal boundaries and democratic governments
  • Confirmation to use AI for positive and constructive reasons
  • A strong foundation for the team to understand the legitimate use of technology

At Censius, we believe that AI is not just a cutting-edge technology that redefines paradigms but a responsibility that can lead to a better society.  

Further Reading

Fairness and Ethics in Artificial Intelligence!

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

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