Monday, December 20, 2021

g-f(2)744 THE BIG PICTURE OF THE DIGITAL AGE (12/20/2021), Computer Weekly, Top 10 artificial intelligence stories of 2021

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"g-f" fishing of golden knowledge (GK) of the fabulous treasure of the digital ageArtificial Intelligence, Top AI stories of 2021 (12/20/2021)  g-f(2)426 

Lessons learnedComputer Weekly 

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Top 10 artificial intelligence stories of 2021

The maturity of artificial intelligence (AI) was evident this year, as the conversations in the industry shifted focus from deployment and innovation to ethics and legislation of algorithms.
  • Businesses are beginning to reap the rewards of strategic AI initiatives, but many questions need to be answered as to how and where it is appropriate to deploy AI systems.
  • Here are Computer Weekly’s top 10 artificial intelligence stories for 2021:
    1. Building better data foundations to make the most of AI
    2. Making machine learning operational
    3. Self-regulation of AI is not an option
    4. Improve trust in algorithmic decision-making
    5. Building better data foundations to make the most of AI
    6. Why a data-driven world should consider an oath of ethics
    7. Europe’s proposed AI regulation falls short on protecting rights
    8. How AI and automation drive better customer service
    9. A bottom-up and top-down look at intelligent automation
    10. The drive towards computational storage

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Top 10 artificial intelligence stories of 2021Cliff Saran, Managing Editor, December 20, 2021, Computer Weekly.


Cliff Saran

Cliff Saran is the managing editor (technology) on Computer Weekly magazine responsible for commissioning, writing and overseeing the magazine strategy concerning all matters relating to technology from up-and-coming research and development to systems management challenges and legacy support and maintenance.

Cliff has been writing about these subjects since the early 1990s. In his current role, he writes a regular blog called Cliff Saran’s Enterprise blog which aims to unravel the hype, weed out the fear uncertainty and doubt spun by the massive marketing machinery in the IT industry.

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Lessons learned, Computer Weekly 

1. Building better data foundations to make the most of AI

  • The UK government’s national artificial intelligence strategy relies on businesses putting in place the foundations for better use of data – EY research highlights the challenges ahead.
    • In September 2021, the government published its inaugural National AI Strategy, an ambitious 10-year vision for the UK’s digital future. As well as the requirement to improve governance and regulation of artificial intelligence (AI), the strategy recognises that increasing resilience, productivity and economic growth will require businesses across the UK to use data much more effectively than they are now.
    • To achieve this, companies in every region and sector need to ensure their organisation’s data is fit for purpose, recorded in standardised formats on modern, future-proof systems and stored in a way that makes it findable, accessible, interoperable and reusable.
    • What are the barriers holding back businesses from building better data foundations, and how can these be overcome? To answer these questions, EY was appointed by the Department for Digital, Culture, Media and Sport (DCMS) to gather evidence to assess the extent of data foundations and the adoption of AI in the UK.
    • The research was based on surveys, interviews and a rapid review of other high-quality reports and evidence. Businesses were asked about the extent to which data foundations and AI were being adopted and the barriers to their use. To ensure that the research was as representative as possible, it included points of view from across the UK economy – from large businesses, to small and medium-sized enterprises (SMEs), and organisations in the third sector.
    • Although our survey showed that 80% of organisations believed that improving data foundations would increase productivity, there is still a sizeable gap between the potential and actual impact of data to drive long-term economic value.

Condensed knowledge

Lessons learned, Computer Weekly 

2. Making machine learning operational

  • As artificial intelligence matures, IT departments will need to take control of change management and governance of data models.
    • Recent research from McKinsey found that the companies seeing significant value from artificial intelligence (AI) are continuing to invest in it during the pandemic.
    • Most respondents at businesses that McKinsey deemed as “high performers” said their organisations have increased investment in AI in each major business function in response to the pandemic, while less than 30% of other respondents said the same.
    • These high-performing businesses were in a better position to meet the challenges of the global pandemic, it said. “Self-adapting, reinforced learning can navigate greater complexity,” said Jacomo Corbo, co-founder and chief scientist of QuantumBlack, an AI consultancy that is part of McKinsey’s advanced analytics business.
    • In his experience, businesses need to adapt the approach they take to building and retraining AI models and the collection of data, to enable greater levels of agility. “We have to collect data in a much more agile way and retrain models with a high cadence,” he said.

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  • Category 2: The Big Picture of the Digital Age
  • [genioux fact deduced or extracted from Computer Weekly]
  • This is a “genioux fact fast solution.”
  • Tag Opportunities those travelling at high speed on GKPath
  • Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
  • Type of validity of the "genioux fact". 

    • Inherited from sources + Supported by the knowledge of one or more experts.


“genioux facts”: The online programme on MASTERING “THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)744, Fernando Machuca, December 20, 2021, Corporation.


PhD with awarded honors in computer science in France

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