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Artificial intelligence (AI) is the simulation of human cognitive abilities by computer systems and machines, enabling them to perform tasks that would normally require human intelligence.
As AI becomes more integrated into our lives and its role in decision-making, in different industries, expands, more ethical issues and concerns are becoming apparent. Primarily, the role of AI is to be of great interest to people and organizations and positively impact them, not the other way around.
The experts and researchers working on AI algorithms are responsible for developing trustworthy algorithms, while maintaining social responsibility.
Artificial intelligence is becoming increasingly popular lately and it is affecting our daily lives in various ways, from purchases or services to choosing a career. It is transforming the way we communicate and search on the internet, as well as providing healthcare services, receiving education, etc.
Nonetheless, there have been many discussions about the impact of AI on society. On one hand, many people support the idea that AI improves the quality of life by making many complicated processes and tasks easier, safer, more efficient, and sometimes even better than humans themselves.
Furthermore, AI has other benefits such as improving consumer experience and enabling them to receive help 24/7, facilitating many healthcare services, improving the lives of people with special needs, enhancing cybersecurity, reducing the consequences of human error, providing higher accuracy of data collection, automating many tasks, etc.
On the other side, others argue that AI poses serious privacy risks, costs a lot, increases unemployment, and other ethical concerns.
While there is no definitive answer to the question of whether AI has a positive or negative effect on our society, it is evident that AI has an undeniable impact.
Ethics of AI represent a set of moral principles and guidelines that advise the development, responsible use, and outcome of AI. They remain a key factor in designing AI tools and they are adaptable to different forms of AI equipment and systems.
According to IBM, there are three basic ethical principles of AI:
Depending on new concerns that might be risen over time, new guidelines may emerge as needed.
Some of the most important ethical challenges of AI are:
AI bias risks the reinforcement of existing biases and stereotypes in the population. It can be hurtful to the already marginalized, vulnerable, and disadvantaged group of people.
However, this concern should be well analyzed as the transformation in the job market is mostly taking a shift from specific roles to another, rather than job loss. The fact that many new jobs and tasks will emerge from AI should also be taken into consideration. AI has still limited capabilities, therefore, it is unlikely to replace many jobs. Furthermore, it requires humans input and it depends on them.
In order to prevent such issues, organizations are implementing privacy information management systems and governments have developed many regulations and laws, such as GDPR, CCPA, etc.
To address such issues, experts have designed frameworks that provide organizations with better protection. For example, ISO/IEC 27001 Information Security Management System, Cybersecurity Management, etc.
In addition to ethics, AI technologists should also consider social responsibilities when developing AI tools. AI technologists are responsible for designing reliable systems that are accurate, easy to use and understand, and that are accessible to everyone. They are intelligent algorithms that prioritize and use the needs of its users to make trustworthy decisions.
Socially responsible AI algorithms aim to address different social and technical issues and enhance AI’s benefits to society. They refer to processes driven by human values, such as:
The role of socially responsible AI algorithms is to:
Socially indifferent AI algorithms, on the other hand, can be harmful to disadvantaged groups or groups that experience a higher risk of poverty, social exclusion, and discrimination, and favor privileged ones, those who already benefit more.
To avoid these problems, it is necessary to have a diverse and representative set of data and training data, as well as to have diverse stakeholders involved in the development and deployment of AI algorithms.
Corporate social responsibility is a self-regulation model used by organizations to be socially responsible, ethical, and valuable to the community. It is a strategy that empowers them and enables them to positively impact the world.
Corporate social responsibility has four main categories:
When it comes to the use of AI, every organization should be aware of and understand its corporate social responsibility. They should use, produce, and offer qualitative services and should recognize their role in the community.
ISO 26000 Social Responsibility is an international standard that provides guidance on how to behave in a socially responsible manner and contribute to society. The importance of social responsibility has increased as the pressure from the world to uphold social standards has grown.
ISO 26000’s seven core subjects of social responsibility are:
As AI impacts all these areas, ISO 26000 is highly related to its development and use. AI developers should carefully consider all these aspects, and they can be guided by the standards’ requirements and guidelines.
Professionals can become ISO 26000 certified, acquire the needed skills and expertise, help their organizations enhance their processes, increase their organization’s awareness on the impact of social responsibility, and help them behave in a responsible manner.
About the Author
Vlerë Hyseni is the Digital Content Officer at PECB. She is in charge of doing research, creating, and developing digital content for a variety of industries. If you have any questions, please do not hesitate to contact her at: content@pecb.com.
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