Ensuring AI stays away from biases that affect human mind

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Ensuring AI stays away from biases that affect human mind
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  • A recent study by PwC revealed that 86% of the respondents stated AI has become a mainstream technology.
  • Blue-chip organizations’ AI recruiting tools have been revealed to be biased against women.
  • Organizations should first develop a methodology for deploying AI technologies to eliminate bias and elevate AI practices.
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Advancements in technologies have enabled organizations across industries to weather the economic storm inflicted by the pandemic. The rapid acceleration of technology especially with the use of machine learning (ML) and artificial intelligence (AI) has enabled organizations to sustain and potentially thrive in today’s economic landscape.

A recent study by PwC revealed that investment in AI has skyrocketed in the past year. Nearly 86% of the survey respondents stated that AI has become a mainstream technology in their firm. While its growing list of applications is undeniable -from enabling organizations to effectively deal with complex and time-consuming repetitive tasks, to identifying growth opportunities for the future— AI is still far from perfect. The perfect example of AI’s drawback is concerning ‘ethics and bias’.

These two elements have garnered AI negative attention from the public. For example, there is evidence of bias against dark-skinned and female individuals in face recognition technology- racial and gender biases are common, it appears. Other examples include AI recruiting tools that showed bias against non-white candidates, candidates of a certain ethnicity, race or language, and women, among many other examples.

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Yet, even with this criticism, many organizations are still not able to address this issue. As per a recent report from FICO, only 20% of the enterprises are actively monitoring their models in production for fairness and ethics. Additionally, 73% of the survey respondents found it difficult to get the support of their executive board for prioritizing AI ethics and tackling bias associated with it.

Biases in AI emerge due to ML based training data which inculcates inaccurate human unconscious beliefs and assumptions into the AI learning module, making its reactions biased.

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An overrepresentation of certain data types can result in a system that can put a greater emphasis on that instead of assigning equal weightage to different data points. Therefore, it is vital that organizations that are heavily investing in AI tools take measures that will help them to eliminate bias while enabling them to establish best practices from the very beginning.

Incorporate the principles of ethical AI

To eliminate the bias and elevate the AI ethics practices, organizations first need to choose how they can develop and deploy AI technologies. They should ingrain the ethical principles of AI such as explainability, security, privacy, and human agency oversight. Doing this will empower them to eliminate the root of AI bias before the technology is deployed to the enterprise-wide infrastructure.

To ensure that AI ethics are followed, the European Commission has launched its first-ever legal framework to set up a precedent for transparency in AI. This framework as per the committee ensures the safety and fundamental rights of people and businesses while strengthening AI uptake, investment and innovation across the EU.

Get the Board on board

As any issues associated with AI may have comprehensive and long-term hazards such as reputational and financial impact, it is of utmost importance to get the board on company’s board to deal with threats associated with AI. Ideally, the task should be the responsibility of the technology or data committee of the board.

To incorporate ethics into AI, organizations should begin with determining what matters most to the stakeholders. Organizations should consider having a committed AI governance and advisory council that includes cross-functional leaders as well as outside consultants that would engage with stakeholders by having a multi-stakeholder group in place. They should establish and oversee the governance of AI-enabled solutions that include their design, development, deployment, and use. Many tech giants have this AI ethics board already set up.
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Invest in diversifying the AI field

Most people have emphasized the point that AI as a field does not encompass the diversity of society that includes gender, geography, race, and physical disabilities. Having a more diverse AI community in place is in a much better position to predict, identify and evaluate issues of unfair bias and engage with communities that are suffering from them. This will require them to invest on multiple fronts especially AI education as well as access to tools and opportunities.

The emergence of new technology always brings associated benefits and risks, and AI is no special case. Therefore, it is up to the enterprise leaders to navigate the intricacies by weighing risks and benefits for achieving their objectives as well as fulfilling their commitment to multiple stakeholders. Even as multiple seeks to capitalize on AI technology to enhance their business performance, organizations should consider the ethical questions raised by this technology and find ways to implement it responsibly.
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