Bias in Machine Learning and AI
Presenting new ethical challenges in business
AI and Machine Learning (ML) technology have become a major part of the armoury for many industries whether it be private companies, financial services, healthcare or governments.
These data driven tools are used to make ever more important decisions that can have far-reaching impact on individuals and societies both positive and negative.
As these solutions have evolved and become more widely used, new human rights issues have been brought to light as biases are uncovered within the decision-making systems we design. This also causes legal, ethical and brand reputation issues for the entity involved.
Beyond Analysis can help you assess your AI and Machine Learning solutions for bias and provide the solutions to remedy this.
Bias in Machine Learning and AI
AI as both perpetrator and champion for diversity and inclusion
The growth in the availability and use of data has led to the pervasive use of rules driven decision making and AI models across many aspects of our lives. For businesses the benefits have been huge. However, what is less well understood is how these tools can inadvertently contain bias.
Beyond Analysis can help you assess your AI and Machine Learning solutions for bias and provide the solutions to remedy this.
Review
Independent review of your models to identify and assess bias
Discuss
Facilitate internal conversations about bias and the outcomes
Fix
Targeted modifications to model or data sources to address bias
Monitor
Implement process of regular review and assessment to check for bias for internal reporting
Watch
Watch our sector based briefing sessions by our CEO Paul Alexander and Bias in data expert Jordan Browne Moore.
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