As the benefits of AI take hold and social issues rise to our collective attention, the need for trustworthy AI principles and practices has gained warranted focus.
In the recent Global AI Adoption Index 2021, conducted by Morning Consult and commissioned by IBM, 91% of IT professionals surveyed say their organizations ability to explain how their AI made a decision is critical.
74% of IT professionals surveyed also report their companies are exploring or deploying AI. This number is likely to rise as businesses accelerate digital transformation.
A proactive approach to identify and counter potential risks is needed to scale AI to its full potential, turning principles into practice.
IBM has made our position known on ethics and leads in workplace diversity, inclusion and equality, with a history of fair and inclusive practices including:
Competitive skills sets are evolving rapidly in today’s environment. To keep up in the workplace, employees and candidates expect consumer-grade experiences and equitable access to opportunity. These consumer-grade experiences require personalization, making AI not a luxury but a business imperative.
IBM has built AI solutions for HR designed to foster trustworthiness and deliver an end-to-end employee experience across the entire employee lifecycle. It helps to redefine how we attract, develop and retain talent to transform the human experience.
Our solutions are designed to deliver personalized experiences, with skills as the silver thread across the employee journey, empowering IBMers to make fact-based decisions. Key experiences are explainable, they empower users to give feedback, and they help identify and mitigate bias.
IBM’s tools help managers build a skilled, diverse and inclusive workforce. Reflected within are IBM’s ethical principles and those of trustworthy AI: that AI augments human intelligence without replacing human decision making; that data and insights belong to their creator; and that AI systems must be transparent and explainable.
The result: Quality of hires rose 10% year-over-year in 2020, and the hiring of US underrepresented minorities rose 20% over the last three years.
AI provides recommendations that managers can choose to use to help them make objective skill-based pay decisions and foster transparent pay conversations aligned with trustworthy AI’s pillars of governed data and AI technology: transparency, explainability, fairness, robustness, and privacy.
Ultimately, managers know their employees best, so while AI provides recommendations, it does not automate the decision. The manager is the decision-maker. Managers view the explanations for these recommendations and may use them to help inform and shape the conversation with the employee.
The result: Attrition was reduced by one-third when managers followed the recommendation.
While it’s important to be thoughtful in how we design and use AI, the more profound impact comes from the experience of IBM employees and candidates. Hearing employee stories of how AI can open doors and help with access to an opportunity is humbling and inspiring.
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