Artificial intelligence (AI) is being used as a tool to support the fight against the viral pandemic that has affected the entire world since the beginning of 2020. The press and the scientific community are echoing the high hopes that data science and AI can be used to confront the coronavirus and “fill in the blanks” still left by science.
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There is little doubt that COVID-19 has been the single most influential driver of our lives and livelihoods in 2020. The impact of the pandemic however has been very mixed for certain groups of society, certain industry sectors, certain companies and for certain technologies. Three key themes emerge around PwC’s Global Responsible AI survey, of over 1,000 C-level executives, conducted in November 2019.
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Responsible AI is a broad topic covering multiple dimensions of the socio-technical system called Artificial Intelligence. We refer to AI as a socio-technical system here as it captures the interaction between humans and how we interact with AI. In the first part of this series we looked at AI risks from five dimensions. In the second part of this series we look at the ten principles of Responsible AI for corporates.
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Model monitoring using a model metric stack is essential to put a feedback loop from a deployed ML model back to model building so that ML models can constantly improve itself under different scenarios.
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Gitanjali Rao, an Indian-American, has been named Time’s first-ever Kid of the Year, 2020. The young scientist uses technology such as Artificial Intelligence to solve world problems. Through her innovations and leadership qualities, Gitanjali aspires to inspire more young people to become innovators.
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Microsoft has filed a patent which raises the intriguing possibility of digitally reincarnating people as a chat bot. Instead of using the conventional method of training chat bots using conversations and material from a wide sample of users, Microsoft’s patent raises the possibility of creating a chat bot from the output of a specific person.
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To date, the organizations have focused on formalizing data consumption practices through distribution technology, access-based delivery mechanisms for analytics, and AI functions. However, with data protection laws and positive awareness across the world, firms have extended the formalization to data collection management. This in-fact is the first life-cycle stage of data.
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While 2021 is approaching, New Year’s Eve period is always a good time to make some considerations about the year that passed and what to expect during the next year in Artificial intelligence.
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