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The sheer volume of real-time data has made it possible to train the Artificial Intelligence models to boost productivity in a cut-throat competitive market. There is an immense impact of Artificial Intelligence on multiple industries across the world in recent years. But, companies in the industries that are dealing with Artificial Intelligence have to be careful about the governance and management of the disruptive technology in an ethical way. Thus, here comes the concept of ethical AI— an ethical framework with four essential elements for effective governance of AI models— fairness, accountability, transparency, and explainability. Let's dig deep into the top companies building ethical AI for a better brand image in the global market.
Top progressive companies building ethical AI to look out for in 2021
Being one of the most popular Silicon Valley tech giants, Facebook is determined to build ethical AI in the entire system. Facebook has some underlying pressure from famous data breach cases like the Facebook-Cambridge Analytica case, fake news, hate speech, and many more. Thus, Facebook has taken this initiative to announce award recipients of the Ethics in AI Research Initiative for the Asia Pacific after partnering with the Centre for Civil Society and Governance of the University of Hong Kong and the Privacy Commissioner for Personal Data in 2019. It has also formed a special ethics team to prevent bias in the Artificial Intelligence software in 2018. It revealed that the company is focused on developing discrete software to ensure the decision-making process as ethically as possible with those four above-mentioned essential elements. The research team has also decided to publish academic papers documenting the findings from the Fairness Flow software as per the transparency principle. Facebook is one of the progressive companies building ethical AI by encouraging research in ethical AI in 2019. It has announced the selection of six projects from India to focus on three key areas— governance, cultural diversity as well as operationalizing ethics such as explainability or fairness. Facebook was also set to create an independent Institute for Ethics in Artificial Intelligence with an initial grant of US$7.5 million for five years in collaboration with the Technical University of Munich, Germany.
IBM is focused on helping people and organizations adopt ethical AI to build systems based on trust. According to IBM's survey, about 78% of senior decision-makers mentioned that it is essential to trust the insights from AI if the outcomes are fair, safe, and reliable for organizations. The pillars of ethical AI at IBM are explainability, fairness, robustness, transparency, and privacy. There is also a presence of the IMB AI Ethics Board that was established as a central cross-disciplinary body to support a culture of ethical, responsible, and trustworthy AI for the IBM ethics policies, practices, communications as well as research for products and services. IBM Research is also determined on building and enabling AI solutions focused on trust.
Apple joined a research group as a founding member for ethical AI with fellow tech giants across the world in 2017 known as Partnership on AI. It is committed to open dialogue about ethical AI through research papers for the public. Apple also organized a podcast on practical AI ethics through Machine Learning and Data Science. Two spokespersons discussed the strategies for how to arrive at ethical AI principles suitable for each organization along with what is involved in implementing the strategies in the real-life work environment. It has another podcast known as Ethics in Artificial Intelligence: Morality and Regulation that covered the importance of ethical training for AI.
Microsoft is committed to the advancement of Artificial Intelligence with ethical principles for its users. The company put its responsible ethical AI principles through the Office of Responsible AI (ORA), the AI, Ethics and Effects in Engineering and Research (Aether) Committee as well as Responsible AI Strategy in Engineering (RAISE). The ethical AI principles include fairness, reliability, and safety, privacy and security, inclusiveness, transparency as well as accountability. Microsoft is putting the ethical AI principles by taking a people-centered approach to the R&D and deployment of AI. It is also focused on helping other organizations cultivate these principles into place from implementation to governance. It also helps to learn the process of developing strategies and principles as per the needs of the organizations. Microsoft provides tools, guidelines, and additional resources to create an ethical AI environment efficiently.
Being one of the most popular tech giants in the world, Google is committed to focusing on ethical AI research with a ten-member team. But the reputation of Google took a dip after it fired two of the eminent research fellows of the Artificial Intelligence ethics research wing. It has promised to double the research staff for building ethical AI efficiently. But the team members are in doubt whether Google is ready to listen to the criticism of the project and consider that ethical AI research has no point if Google continues to silence criticisms. Google held up the promising ethical AI research team for more than three years in addressing critical issues. Meanwhile, Google has established several efforts to encourage ethical AI since 2018— training based on the Ethics in Technology Practice project, AI Ethics Speaker series, and the technical module on fairness to the free Machine Learning crash course, and many more.
TCS has promised to ensure safe, secure, and sustainable AI models for better customer engagement in the global market. It considers six Rs to follow the ethical AI principles— rational, righteous, reliable, revitalize, restrictive along with ROI and results. TCS considers that ethical AI will be one of the potential reasons to drive business revenue in the upcoming years. It uses the concept of the Machine First Delivery Model (MFDM) to address ethics in AI services and solutions. Ethical AI models harnessing MFDM ensure to be more human-centric, transparent, explainable, fair, safe, and trustworthy. The integral function of MFDM is to provide the utmost solutions to organizations by balancing ethical challenges and implementing guidelines.
