Note: Examples here are just for illustration, they may not tally with real time events. Note real facts on historical events may vary.

Here is my lecture on AI based E-governance.

Key Points in the lecture

— E-governance is there for long but we need AI based E-governance more than ever before now. These databases can be statistically analyzed, but we need to go beyond statistics. These databases can be analyzed with data mining, we need to think beyond data mining as well.

— Why AI and why to use AI, why to pay prize to do AI based analysis of E-governance data?

— Is it to save money? To automate systems?

— Is it to layoff people? No, if you think so, you are mistaken, if someone does it then he is getting it wrong, at least for the government.

— It is to understand what processes are being struck and what are the problems learning from the past and learning from each other, country-wise, state-wise, and globally, which shared data.

— How to get out of tough or deadlock kind of problems.

— Its not just to save the jobs or to lay off the government jobs.

— Is it about saving the government money.

— Its about how to get out of the problems that the governments get struck into.

— What we did earlier and what we should do now?

— And AI based help to get out of those problems.

— The aim of AI here is to use artificial Intelligence to get out of some problems, with say right prompt.

— Human intelligence is also there but the problem is that systems are so many, managing everything humanly is not easy when decision-making is complex. Only experienced politicians can do such decision making, but to reach seniors with each problem is not tough so lets have seniors with us, with the learned AI-systems.

— Example the flood thing that happened, that was missed humanly, AI might had been able to help then if it were guided and well trained AI.

— That letting officials know certain things are to be escalated, these things are not in domain of even AI, so let experts handle it.

— In Spain floods, these issues would had to be escalated and it had to deal with loss of lives and materials.

— Its not about job loss and automation, as we progress further in life, the problems changes and we lead to ultra modernization, where life need to be preserved.

— It should not take job, rather upskilling should be done.

— These people have experience of government departments, so they can apply AI, monitor AI growing on tasks they are good at.

— If they are master of some task they can apply AI on that task and it can be useful.

— The can master tasks, in future if there is a four day a week concept or a three day a week concept, then it is ensured AI is back there and can escalate things to you, to come to office or more. For example airforce pilots are ready to work day and night, and at times have no work at all. Same way the Spain floods that water that fell in in Spain, such things come under accountability. The things to escalate and handle things need to be developed and AI can help in that, saying why are you not taking the feedback from the next level. The human officer will say “why do I need to do it”, AI system would say, “something is not right here, something like this happened in Afganistan in yes xxxx, and they took xx steps. I have checked with Afganistan metrological department” .

This is the level of AI we want to build

— These are topics of accountability and transparency.

— There are some departments that can be shared for AI for global welfare, such as climate change, natural calamities, metrology and more.

— Everything is electronic governance, all these things E-governance and metrology, are in electronic forms not, lets see how E-version of climate change develops.

— Interactions and exchange around the world needed.

— -World can be a much smaller place to live in as all this can be shared.

— Yes E-governance things cant be shared.

— Example of AI that can comes out of sharing E-climate change data can be like, “This happened in xyz town and they did not take steps, so it made abc number of casualties”

— This is just one example of how world would be one place when dealing with climate change with help of AI.

— Worldwide all the climate change data and all the natural disaster data can be shared to be used by common AI.

— Human can be constantly reminded by AI such as “These events happened in Japan and these events happened in Turkey”. Nobody was prepared there as well, nobody ever thought that such a thing could had happened. Were there any hints? Now this can be connected to the geological data. If something like this happens, what to do next, for the entire area, AI based messages and AI alerts can be send.

— So transparency is that we had a record of Spain data, we had Afghanistan data, but things happened. (This is just for illustration, do not correlate)

— There are supervised and supervised learnings but we need deep learning too.

— Its not just supervised algorithms no, there should be logic also, there should be decision making also, there should be uncertainty based decision making as well, there should be CNN, LSTM, GPT, so on and not to forget Expert Systems.

— Country-level E-governance data cannot be shared. Thats privacy.

— E-governance of the country should be free from data theft.

— For example the country’s taxation data should be within the country only. Questions the leaders can ask is are people feeling burden, not just statistics, its more than statistics, not just data mining, its more than data mining,

— This is not for decision-making, this is for inputs.

— You can give prompts, prompts, “Are people happy with current taxation systems”

— Are people happy with goods and services tax.

— Can leaders increase some tax, as country is in need of some money, such kind of questions in Natural Language Processing should be made.

— Next, example, of AI based E-governance, to maintain international relations, for example two countries were not in good friendly international relations, AI can help find out good times, and come up with ways of dealing it with and to send solutions to bureaucrats who can implement the same. For example India and Canada are not in very nice happy relation these days, so some old quotes can be recalled, and some solution can be found with government GPT, or Diplomat_GPT

— Next example, is, the benefit of your own citizens, for example in India there are farmers that are protesting, online protest was a topic of my article sometime back, here its different, but people need a medium to say and be heard.

— Self trained chatGPT like solution along with logic.

— Constitution GPT, legal GPT,

— An intelligent AI for solving such problems.

— Prompt, who is most unhappy, and why,

— Who is the happiest?

— Deep learning GPT is not enough, logic is needed,

— GPT has entered in a plateau region, progress needed here,

References

1 — https://www.youtube.com/watch?v=AfETwg3SlnM

To be continued……