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Current AI elaboration area and future scope.pptx
- 1. AI in Governance: Why, What and How AI in government and public services — now and in the future Current AI: AI is rapidly evolving, but it's important to remember it's not some super- intelligence yet. Today's AI excels at specific tasks involving data analysis, pattern recognition, and automation. Surya Basnet Machine Learning and Data Science Community Nepal https://mldsnnepal.org
- 3. Four Phases of E-Government Mode
- 4. More people are connected (Internet, Web, Social Media, IoT) More machine intelligence is available More data is available (Big data, Open data, Linked data, Blockchain) 2030 2010 ● Citizen Services: Chatbots and virtual assistants can answer questions, guide people through processes, and even personalize service delivery. ● Data-Driven Decisions: AI can analyze vast datasets to identify trends, predict problems, and inform policy decisions. Law Enforcement: AI can sift through evidence, identify patterns in crime data, and even predict potential criminal activity
- 5. From Industry 1.0 to Industry 4.0
- 6. Industry 4.0
- 7. Government 1.0 Division of labor, rules of Economy, French Revolution, US Constitution Post Kingdom - democracies 1789 1870 1950 Government 2.0 Processes, Bureaucracy, Management Science, Workflow, Project Management, Logistics, Typewriter Post-Empire Democracies Government 3.0 Computers, Information Systems, Software, Service science, Interoperability Standards, Mobile devices Postwardemocracies Government 4.0 Cyber-physical Systems AI, IoT, Smart solutions, Bid Data, Analytics, Policy modelling and simulation, stance classification, opinion mining, sentiment analysis New forms of Democracy ? dGOV1.0 dGOV2.0 dGOV3.0 Connected Open Smart/ Disruptive Governance Governance Governance From Gov 1.0 to Gov 4.0
- 8. The Domains of Digital Governance Digital Governance Digital Governance 1.0 (Service Provision) Digital Governance 2.0 (Open & Collaborative Governance) Digital Governance 3.0 / 4.0 (Smart & Disruptive) ServiceAutomation and BPR Legal, Organisational, Semantic & Technical Interoperability e-Authentication Digital Signatures Service Portals Mobile applications Cloud Infrastructures Big Data-Driven Decision Making Artificial Intelligence in Governance e-Participation e-Voting Open Governmental Data (OGD) Linked Data e-Collaboration (Collaborative Service Design) Crowdsourcing Community Awareness Platforms Blockchain in Governance Internet of Things Policy modelling Societal Simulation Opinion Mining / SentimentAnalysis
- 9. PwC 4 Adoption> AI is automating, transforming, and disrupting all industries Value> AI is projected to contribute significant value to global GDP Operationalize AI > AI is moving from proof-of- concepts to operational systems Responsible AI> Responsible use of AI is gaining increased attention AI as a National Competitive Advantage> Countries are developing AI strategies to gain national competitive advantage Investments> Dramatic rise in deal value & volume is reshaping AI
- 11. AI Can be Explored Agriculture Health Education Construction Food and Beverage Fintech Logistics Retail Sports Automative Energy Life Sciences Manufacturing Software and Internet Gaming Why The AI market is huge: The current global market for AI is expected to hit $42.6 billion by year's end. And that's just the start: consulting firm PwC forecasts that by 2030, AI will contribute $15.7 trillion to the global economy Explored Area Can Be:
- 12. Opportunities, Threats, Future of AI and Government Jobs Opportunities: ● Boost Efficiency: Automating repetitive tasks frees up government workers to focus on more complex issues. ● Improve Transparency: AI can analyze data to identify and root out bias in decision-making. ● Enhance Public Safety: AI-powered crime prediction can help allocate resources more effectively. Threats: ● Job Displacement: Some government jobs with repetitive tasks might be automated. ● Algorithmic Bias: AI systems trained on biased data can perpetuate those biases in decision- making. ● Privacy Concerns: Large-scale data collection for AI raises privacy and security risks. Future of AI and Government Jobs: The future is uncertain, but it's likely AI will create new government jobs while automating some existing ones. The key will be to: ● Reskill and Upskill Workers: Governments need to invest in training programs to help workers adapt to the changing landscape. ● Develop Ethical Frameworks for AI Use: Clear guidelines are crucial to ensure AI is used responsibly and fairly.
- 13. Future & Recommendations Autonomous Vehicles & Robots Soft-Bots & Chatbots Digital Twins Societal Modelling Self-adapting Simulation Automated Reasoners Intelligent Systems Large Corpus Understanding Decision Support
- 15. Artificial intelligence (AI) market size worldwide in 2021 with a forecast until 2030(in million U.S. dollars)
- 16. AI Initiatives in Nepal 1. Community called machine learning and data science network (MLDSN) Nepal in 2018. https://www.mldsnnepal.org/ 2. Naami Nepal Started in 2018 AI Winter School https://www.naamii.org.np/outreach/annual-nepal-ai-school/ 3. Fuse Machine Nepal Democratize AI https://fusemachines.com/ 4. Infusion AI-Driven Technology for Tomorrow’s Success https://treeleaf.ai/ 5. Kathmandu University Started BTech AI and Mtech AI program in 2021 6. Tribhuvan University Department of Mathematics Started Master in Data Science Program Many more college and university have also started to teach AI and Data Science related program
- 17. Thank you Q & A ?
Editor's Notes
- Current AI: AI is rapidly evolving, but it's important to remember it's not some super-intelligence yet. Today's AI excels at specific tasks involving data analysis, pattern recognition, and automation.
- Areas of business that will require the most AI skills over the next year as of 2023 Published by Bergur Thormundsson , Feb 8, 2024 Generative AI and prompt engineering are the areas of business that will require the most AI skills over the next 12 months per a survey carried out in the middle of 2023. This follows the trend of 2023 where generative AI took off from its humble beginnings as an art generator and has now reached into major industries like teaching and law. Artificial intelligence solutions spending share APAC 2022, by sector Published by Statista Research Department, Nov 8, 2023 In 2022, banking, financial services, and insurance made up nearly 28 percent of the spending on artificial intelligence (AI) solutions in the Asia-Pacific region. Professional services accounted for eight percent of the total spending on AI solutions in the region in 2022. Generative AI adoption in global companies 2024, by function and expertise Published by Bergur Thormundsson , Feb 28, 2024 The functions related to product development, IT and cybersecurity, and marketing, sales and customer service are where most of the generative AI (GenAI) adoption is concentrated in global organizations. The use of the technology is the highest in higher levels of expertise. Over 50 percent and 70 percent of the respondents, with respectively high expertise and very high expertise, report to be using generative AI in a limited or at-scale implementation.
- https://www.linkedin.com/pulse/industry-10-40-ayush-kumar/
- Global mobile cobots market volume 2021-2030 Published by Bergur Thormundsson, Aug 22, 2023 According to Next Move Strategy Consulting the market for mobile cobots is expected to show strong growth in the coming decade. With around three thousand units shipped in 2021 is expected to grow considerably by 2030, up to nearly 43 thousand units. Mobile cobots represents a diverse markets and is classified as all robots that work alongside humans without the need for demarcated safety lines. Possibly the best example of this would be Amazon warehouse robots that ship and move pallets for warehouse staff. Collaborative robots worldwide - statistics & facts While it might sound like something out of Star Wars it is a fact that robots enable industries to lower production costs while improving the quality of their products and increasing productivity. The adoption of collaborative robots, or cobots, is one of the ways to achieve these goals. Driven by the trend of industrial automation, cobots are a fast-growing segment within the broader robotics market. Between 2022 and 2030, cobot shipments worldwide are expected to grow exponentially, from around 4,500 in 2022 to 42,000 in 2030. Most of the cobot shipments are destined for the electronics and automotive industries. Correspondingly, the global cobot market is expected to grow in terms of revenue as well. Valued at some 900 million U.S. dollars in 2022, the market is projected to almost triple in the coming years, reaching the size of over seven billion U.S. dollars in 2030.
- According to Next Move Strategy Consulting the market for artificial intelligence (AI) is expected to show strong growth in the coming decade. Its value of nearly 100 billion U.S. dollars is expected to grow twentyfold by 2030, up to nearly two trillion U.S. dollars. The AI market covers a vast number of industries. Everything from supply chains, marketing, product making, research, analysis, and more are fields that will in some aspect adopt artificial intelligence within their business structures. Chatbots, image generating AI, and mobile applications are all among the major trends improving AI in the coming years. Generative AI a growing market In 2022, the release of ChatGPT 3.0 brought about a new awakening to the possibilities of generative artificial intelligence. A good understanding of this trend comes from observing the difference in interest in generative AI on Google, with interest growing rapidly from 2022 to 2023. It is to be expected that this interest will continue as both ChatGPT and others aim for updated chatbot versions in the future and further generative AI programs are in development. Growing awareness in academia AI has long been a fast-moving field, with specialists in academia having to keep up with rapid technological developments. Most specialist PhDs in North America, for example, go to work in the industrial sector, with barely half that number going to work in academia. Therefore, traditional academic writing on the topic of AI has consistently been behind the times, as the academic process takes time. A change in this trend can be observed as more and more publications on the topic come out.