As artificial intelligence (AI) continues to play a significant role in various industries and aspects of daily life, the issue of bias in AI algorithms has become increasingly prevalent. Biased AI systems can perpetuate existing social inequalities and lead to unfair treatment, creating a critical need for addressing and mitigating discrimination in machine learning applications. Bias in AI can originate from several sources, such as biased training data, lack of diversity in AI development teams, and biased algorithms themselves. Training data is the foundation of any AI system, and if the data used to train an algorithm contains biases, those biases will be passed on to the AI system. For example, biased facial recognition systems have been found to misidentify people of color at a higher rate than white individuals, leading to wrongful arrests and other consequences.

Embedded AI: Start paddling now -- one in five organizations will double down on "AI inside." During the pandemic, digital natives effectively used "AI inside" -- AI that's embedded at the core of everything from architecture to operations -- to bridge the business-to-customer divide in areas such as grocery delivery and restaurant supply-chain optimization. In 2022, we expect traditional businesses to adopt this AI-first approach to platform and digital transformation. The more "AI inside," the more enterprises can shrink the latency between insights, decisions, and results. Responsible AI: Don't overlook small waves -- the market for responsible AI solutions will double.

From privacy and surveillance to fairness and transparency, Avanade Ireland's Graham Healy discusses what leaders need to think about when it comes to digital ethics. As digital transformation accelerates, there are plenty of issues for leaders to contend with, from considering a remote workforce to a decentralised data management system. However, there are also ethical issues to consider when it comes to digitalisation, including data privacy, transparency and accessibility. According to Graham Healy, the areas on which leaders need to focus their attention depends on several factors, including the business they're in. Healy is the country manager for Avanade in Ireland, a joint venture between Microsoft and Accenture that delivers digital, IT and advisory services to clients all over the world.

Protected attributes (examples): Ethnicity, Gender, Sexual Orientation, ... 5. When is a process discriminating? Disparate Impact: Adverse impact of a process C on a given group X?