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A Study on Ethical Considerations Embedded in AI Systems

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A Study on Ethical Considerations Embedded in AI Systems

See the author's thoughts on ethical considerations embedded in AI systems.

· AI Zone ·
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Computer intelligence or machine intelligence started influencing the fields where the human cognitive structure had significant roles. When we are on the move with the technical progress, we often forget to nurture certain values and ethics. In our everyday life, we make ourselves too dependable on this artificial cognitive structure.

Artificial Intelligence and Ethical Approaches

Artificial intelligence is a branch of science where human actions are replaced by computers with better completeness. All that matters here is the speed and predictability of the system. The system collects the data, processes it, and gives insights. 

There are chances for the wrong judgment when confronted with unfamiliar situations. What works here is all about the input the AI developers or designers provide. The system only processes based on this input. It can’t understand and act according to real emotions. AI systems analyze the given inputs based on behavioral patterns.  

It is time to discuss the virtues that everyone should possess when dealing with AI. As AI systems need to be predictable and ensure trust, ethical considerations are also to be approached seriously. Let’s check out how human ethics are embedded in artificial intelligence. 

You might also like: Responsible and Ethical AI — Building Explainable Models

Accountability in AI

The cognitive structure of an AI system is developed by humans. The AI designers or developers are responsible or accountable for any actions or recommendations of the AI system. From the initial stage of development to the executing stage, every step is designed and developed according to human logic. The system will respond to various situations based on this input. 

Success and failure, everything will be according to the input given by the developers. How the system will make decisions and how it will create an impact in the world is directly influenced by the developers’ cognitive structure. These developers, or the company, must be accountable for the results created in the world by the AI systems. 

Proper policies and guidelines should be made to handle the issues of accountability. The companies need to follow international laws and regulations. There is also a need to develop standards and certifications for creating an ethically programmed AI system.

Value Alignment for AI

Value alignment is a promise indicating when the AI systems predict, come to conclusions, and give necessary recommendations for decision making. This should be matching with our values and ethics. Values are subjective and are specific to different user scenarios. When users are able to understand AI’s actions, the values are aligned. 

Our experiences of the past, our memories, the social and moral norms that upbringing us all influence the value alignment. A machine cannot process these values or experiences, and a third party needs to impart these values in the machine. It is to be attended carefully to ensure the core values.

AI systems should be developed considering the emotions and experiences of the user group, as these systems can’t draw real insights. Contextual analysis of various experiences by a user group is vital for giving the desired user experience. AI systems are to be developed with deep research on various use cases.

Explainable AI

AI needs to prove its explainability on how people can understand. The methods and techniques used in the application of an AI system must be explained. AI developers and users need to understand the results of AI actions. User experience and explainability need to be well-ensured.

In a normal scenario, people trust the AI system when it proves its capabilities in decision making and recommendations. An AI user should be able to get a clear understanding of why or how the AI is performing actions. All the actions and decision making should be reviewable, especially when handling sensitive data regarding personal matters of individuals.

When AI makes sensitive decisions, the system needs to explain the recommendations and data used to the user. The users are given the right access to verify the process and actions of AI. This will ensure safer practices and improve the social acceptability of AI.

Unbiased AI

How will AI bring fair acceptance? As the AI system is human-designed, there are chances to influence human bias in AI systems. It needs to be attended properly. The AI developers have to do deep research and ensure there are no such biases appearing in the algorithms they develop. 

AI data needs to be analyzed in real-time in order to identify bias and to ensure fairness. Some sort of bias appears intentionally or unintentionally. The developers must make a proper analysis and find out the reasons behind its origin and find a solution to minimize the effects. Reviews by the team will help to identify intentional and unintentional biases. If users are also given a chance to share their feedback or comments, biases can be limited to a big level. 

To mitigate bias in AI systems, we must take steps to make wider participation by including people from different cultural groups, age groups, education fields, etc. This wider participation helps AI developers to identify and minimize biases. 

Business Intelligence and AI — Data-Driven Approaches for Real Solutions

Organizing your business data for intelligent decision making is the key way to bring business to the expected growth. The data is important in the AI system and the information extracted is used to make accurate decisions. Business intelligence tools help to find patterns and help improve performance. Business intelligence defines the use of data more accurately, while AI is data-driven in its form.   

A company, X, seeks the aid of AI for managing the mundane workloads and meeting targets of its employees. The company needs to make smoother communication with the employees, analyze their performance, and find ways to utilize their effort and energy. 

With BI tools, the company introduced personalization and helps employees to effectively manage their tasks and fulfill their work goals easily. The employees get recommendations of actions to take and it encourages them to perform with more accuracy. The behavior of each employee is analyzed and recommends suggestions without harming the ethical values.

With business intelligence tools, the company can understand the key performance of the employees and make intelligent decisions for improvements. BI tools also help the company to track and analyze all the actions of the employees in the company. The insights and reports that are generated using BI tools allow the company to increase productivity.  

Final Thoughts 

When all these focal points are embedded in an AI system, the AI architects can mitigate the bias and make better improvements in further developments. If flexibility is maintained, an AI system can overcome any ethical challenges.  

User experience and giving high priority to user rights are important. Users should have proper access to their data and should be given full control over their data. If users are ensured, how their personal data is used, what conclusions are arrived from their data, the system will be more accepted. When proper security practices are applied for protecting sensitive personal data, human ethics can be properly embedded in AI.

Further Reading

The Path to Ethical AI: Major Obstacles and Solutions

Friend or Foe? Five Ethical Questions Raised by AI

Topics:
artifical intelligence ,ethics in ai ,ai biases ,ai ,biased ai

Opinions expressed by DZone contributors are their own.

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