AI Bias Poses Risks to One-Third of Businesses, Sparking Calls for Increased Regulation from 81% Leaders
AI Bias Harms Over a Third of Businesses; 81% Seek More Regulation
AI bias is increasingly impacting the corporate landscape, with many businesses calling for enhanced regulatory measures to combat this issue. This insight stems from the “State of AI Bias” report conducted by DataRobot in collaboration with the World Economic Forum and various global academic institutions. Over 350 organizations across multiple sectors contributed their views for this study.
Kay Firth-Butterfield, Head of AI and Machine Learning at the World Economic Forum, stated, “DataRobot’s research highlights a reality that those in the AI domain have recognized: the definitions of ethical AI solutions have remained vague for too long. The feedback from CIOs, IT directors, data scientists, and development leads in this research reflects a profound awareness of the ethical implications and consequences associated with AI.”
Approximately 54% of respondents expressed “deep concerns” regarding the risks posed by AI bias, while a significant 81% advocated for increased governmental regulations to help mitigate such issues. Despite AI being relatively newly adopted by many organizations, a disturbing number report adverse effects due to bias.
More than a third (36%) of the organizations reported experiencing challenges or direct negative consequences from AI bias in their algorithms, leading to issues such as:
- Lost revenue (62%)
- Lost customers (61%)
- Lost employees (43%)
- Legal expenses due to lawsuits or legal actions (35%)
- Damaged brand reputation/media backlash (6%)
Ted Kwartler, VP of Trusted AI at DataRobot, noted, “The central hurdle in eradicating bias is comprehending why algorithms make specific decisions. Organizations require direction for navigating the complexities surrounding AI bias. While progress has been made, such as the EU’s proposed AI principles and regulations, further steps are needed to ensure algorithms are fair, trustworthy, and transparent.”
The report identified four primary challenges facing organizations in addressing bias:
- Understanding decision-making processes of AI
- Recognizing patterns between input values and AI outcomes
- Creating reliable algorithms
- Selecting appropriate training data for AI
Fortunately, an expanding array of solutions is becoming available as the industry evolves, helping to address and diminish AI bias. Brandon Purcell, Forrester VP and Principal Analyst, projected that “the market for responsible AI solutions will double in 2022.” He explained that these solutions assist companies in transforming AI principles, such as fairness and transparency, into standard operational practices. Interest in these solutions is set to grow as they begin to penetrate various business sectors beyond those that are highly regulated.
If you’re interested in learning more about AI and big data from industry experts, consider attending the upcoming AI & Big Data Expo series, with events scheduled in Santa Clara on May 11-12, Amsterdam on September 20-21, and London on December 1-2.
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