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2018 Agenda

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The Conference chair will deliver the opening remarks and orchestrate discussions during the day.

  • Building on the government’s reputation as an international hub for AI innovation
  • Providing £20 million of funding to help the UK’s service industries, including law and insurance, with new pilot projects to identify how AI can transform and enhance their operations
  • Boosting AI skills and data driven technologies to continue to build a Britain that is shaping the future
  • Establishing a new £9m centre for data ethics and innovation to examine the possible structural changes to jobs, data privacy and safety that could result from the new technology
  • Allocating £300 million of government funding for AI research to make the UK a global leader in this technology

  • Reviewing the development of process automation within various government bodies to scan and review operating processes
  • Exploring the wide range of opportunities for back office and case processing management
  • Enabling central government departments realise significant productivity gains and its impact on the civil service workforce, focus on more value-added services
  • Extracting insights and developing business cases to secure funding

  • Taking the lead in how data innovation serves its’ citizens, as London approaches 9 million residents
  • Improving digital collaboration and sharing between London’s 33 local authorities and city hall
  • Developing a ‘London Office for Technology & Innovation’ (or LOTI)
  • Supporting collaboration on the design, standardisation and scaling of digital services and smart technology in public services
  • Understanding the City Data Analytics Programme within LOTI; a hub for developing and supporting data science collaborations between public services in London
  • Supporting the use of data for better decision making, policy development and urban experimentation

  • Realising the role of AI in education
  • Understanding the future of predictive learning for teaching professions
  • Considering the relationship between man and machine

  • Initiating a collaborative effort amongst the GDS, ONS, and the Government Office for Science to help the government achieve its full potential in data science
  • Opening the data science campus to build capability through effective training and act as a hub for increased investment in data science research
  • Expanding the Data Science Accelerator Hub programme to give government analysts the ability to develop their data science skills in a real business setting
  • Supporting Data Scientists across government to deliver best practice work by developing and disseminating data science standards, guidelines and frameworks

  • Collaborating with the Information Commissioner’s Office to develop a framework for explaining processes, services and decisions delivered by AI, to improve transparency and accountability
  • Advising the Department for Digital, Culture, Media and Sport on the recently announced Centre for Data Ethics and Innovation
  • Partnering with the Office for National Statistics Data Science Campus to develop dedicated training to grow the data profession and community in the civil service
  • Using these technologies to improve the provision of public services, to design more effective policies, and to measure policy outcomes more accurately
  • Understanding the application of AI and Data Science tools across the NHS and Local Government

  • Embracing the value and importance of a diverse workforce for AI, and should work together to break down stereotypes and broaden participation
  • Considering the leadership and cultural change needed to achieve upskilling the public sector workforce and introducing more agile and collaborative ways of working for data scientists
  • Providing strong leadership by developing a clear career model and development for data scientists
  • Developing the skills, resources and project management training needed to exploit the opportunities offered by the explosion in digital data
  • Addressing the skills gap: Understanding how the EU exit will create the need for more 346,000 more data scientists by 2020
  • Discussing the need for GDS’ investment of £450m annual budget embedding data analysts and scientists in councils
  • Establishing a list of 10 principles that will enable machine learning and embed good practice for service automation

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3:15 pm
3:40 pm
Using Machine Learning to Spot Marine Hazards
  • Collecting data from satellites, overland drones, underwater autonomous vehicles, survey ships to develop geospatial libraries
  • Understanding how the UK Hydrographic Office uses cloud and python to train models
  • Using deep learning to process and identify objects in satellite data
  • Expanding on the partnership with the Data Science Accelerator and other opportunities to build data engineering capability
3:40 pm
4:05 pm
DIY AI: Building Prototypes to Drive Innovation in Government
  • Developed a prototype of a system that can allocate correspondence to the teams which are best placed to answer it
  • Machine learning had been developed to sort parliamentary questions by the team which is required to draft a response, with 90% accuracy
  • Analysing a pool of 5,000 entries to train a neural network to recognise parliamentary questions
4:05 pm
4:30 pm
A Machine-Learning Driven Drug Discovery: A Case Study from Parkinson’s UK
  • Deploying AI capabilities to reason, deduce and suggest entirely new treatments for Parkinson’s
  • Combining the charities’ extensive knowledge of the disease and our world-leading knowledge graph platform
  • Exploring how AI tools can repurpose existing drugs to accelerate drug discovery for Parkinson’s
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3:15 pm
3:40 pm
Utilising AI to Improve the Detection of Fraud
  • Developing the next generation artificial intelligence and data science tools to look at the security challenges faced by large business and government organisations
  • Using a combination of new and established artificial intelligence, network science and machine learning techniques to improve the identification of fraud
  • Expanding the scope of the project to intrusion detection for cyber-security, and detecting faults in safety monitoring systems
3:40 pm
4:05 pm
Capitalising on AI technology to Save Millions of Pounds and Generate New Streams of Revenue
  • Rolling out a digital strategy with embedded AI features that has resulted in savings of millions of pounds over the past five years
  • Developing automated online services that has now started generating the council income
  • Creating a digital platform which combines data with intelligent systems, resulting in fully integrated and automated transactions for all customers
  • Introducing AI and AI powered voice control which, over time, will automate responses to increasingly complex customer demands while reducing officer time and cost
4:05 pm
4:30 pm
Building a Central Data Platform to Develop a Single, Trusted Source for all Regulatory Energy Data
  • Improving the way we manage, store and analyse data and giving us the capability to apply data science and AI techniques
  • Exploring the possibility of sharing this technology and data with other regulators or across industry
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3:15 pm
3:40 pm
Gaining Insights into HMRC’s Data Analytical Model for Managing Tax Compliance
  • Mapping Risk through data mining practices to improve and increase tax compliance
  • Using a dynamic benchmarking model to identify outliers in the HMRC databases
  • Identify the riskiest cases for intervention from VAT traders through the use of predictive analytics
  • Exploiting big data to automate the process of tracing down residential or commercial addresses at risk of undertaking undeclared economic activities
3:40 pm
4:05 pm
Harnessing Predictive Analytics to Forecast Demand in the NHS
  • Developing tools for cross-sector NHS data linkage and analysis, AI and machine learning
  • Harnessing text analysis and use of social media data for predictive analytics in health
  • Analysing trends in healthcare demands to prepare for a crisis response
  • Exploring how Big Data can be harnessed to provide insights into healthcare and direct strategy for better service delivery
4:05 pm
4:30 pm
Aligning Digital and Data Analytics with Corporate Strategy
  • Establishing Woda, a lean start-up jointly funded by the NHS, Police, County, Districts and Fire and Local Enterprise Partnership
  • Using data to deliver critical improvements to multi-agency service delivery
  • Leading the change – people, capabilities, and governance
  • Understanding key learnings and next steps