ARTIFICIAL INTELLIGENCE; ESSAY & GS-[ 1+2+3+4] AND ISSUES WISE

AI FOR GOVERNANCE

Q.) It is time to think of expanding the usage of AI to newer areas, AI Driven Governance-Concept to Practical Application’,? ELOBROTAE.

Global consensus is required in formulating regulations for using Artificial Intelligence (AI) in governance to face emerging challenges such as copy rights, data protection, and cyber vulnerability issues,

the TAMIL NADU Health Department, in 2022, had introduced AI in diagnosing tuberculosis in six districts in the State. “

45 mobile vans fitted with digital X ray machines to go around in remote and inaccessible areas.

Out of these, six vans have been fitted with an AI tool, and more than 56,000 people have been screened by this tool in the last two years.

The rate of detection, in comparison to the traditional models, is twice, and it is as precise as it would be done manually.”

we can do to prevent elephant deaths on railway tracks in Coimbatore district,

where the railway tracks pass through the forest and divide two reserve forest patches.

Elephants migrate from one patch to another to drink water and forage.

There were accidents resulting in the death of elephants. But AI came to rescue,”

health sector, AI had the potential to play an important role in screening refractive eye er rors among children and detecting pregnancy-induced hypertension (PIH).

need to build adequate digital in frastructure.

AI is not a single technology, but a slew of different things.

We don’t need AI to solve all problems. We have to figure out what is the right solution that we need, especially in governance… What we see in most of the places where AI has made an impact, the actual AI solution itself is about 20 to 30% of the system.

caution pushing the current state of AI models into governance would institutionalise models and is likely to ignore our cultural map. “

We can talk about building AI models for the Indian condition.

But we need to put in a lot of effort trying to build these safe guards for India.

There is so much that is unique, like language, cuisine, literature to every State and region in this country that we need to capture.”

the Union government is planning to set up an AI safety institute soon.

India has taken the lead in getting a global consensus on AI in governance.

“The bias, fairness, and risks have al ways been there since the birth of AI.

But new things which came because of generative AI are copyright issues, data protection is sues, and cyber vulnerability, and they require global consensus…

From the Indian context, we have to be very careful because we should not be exporting the data. Data protection, usage, and localisation are extremely critical.

we should ensure that we as a country do not be come digital slaves.”

only the United States of America, China, and India have the potential to create AI technologies. “

The U.S. has al ready created AI.

China is in the race.

India is the potential third country which can make a meaningful contribution to global AI.”

“The accuracy of the output that AI pro vides depends on the amount of data fed.

In this context, we are already witnessing the digitisation in government sectors that is yielding results in terms of the efficiencies in consuming various services…

Indians are the largest consumers of generative AI to day.

But we should explore how India can become a generator of AI technologies rather than consuming it.

Even if we are consuming the data, we should explore to localise it to the Indian context.”

BIG INVESTMENTSCOMMITTED ON DATA CENTRES : ‘Data Centres in the age Of AI: Enabling Scalability, Security and Sustainability’

In the last four to five years, the term ‘data centre’ has come to the forefront primarily because of the high demand for this infrastructure setup, especially after COVID-19, when the adoption of cloud increased,
Huge investments are being committed on data centres,
new generation data centres were launched by Sify in Chennai, Bengaluru, and Mumbai.
DATA CENTER - At its simplest, a data center is a physical facility that organizations use to house their critical applications and data. A data center's design is based on a network of computing and storage resources that enable the delivery of shared applications and data. The key components of a data center design include routers, switches, firewalls, storage systems, servers, and application-delivery controllers.

Environmental footprint

issue of water consumption in the industry,“One thing that the data centre industry is doing, and we are also doing at Sify, is that net footprint on the environment has to be minimal, and need to do it in a sustainable manner.
That means water is not a mandatory ingredient for the data centres, especially the clean water is not something that is must for the expansion of a data centre.
here is enough technology and enough development happening where we don’t have to rely on clean water.”

TRANSPERANCY AND TRACEABLITY
models must be transparent for better traceability and enable users to interpret the decisions made, .
‘Ethical Considerations in AI: Navigating the Moral Land scape’ Highlighting how AI is used to maintain electronic medical records and assist in solutions to build diabetic retinopathy, there were challenges in addressing synthetic data.
Besides validating the data used for decision support system, clinical stakeholders are explained about the outcomes.
AI algorithms are used for credit scores for loans and its assistance is sought with data patterns for credit assessment,
AI gave an insight into data analytics to develop a decision support system on water storage.
It helped in preparing a gist of large tender documents and ensure quick decisions.
AI is a non-linear model and vigorous testing process would help arrive at a reliable model.
Students are taught to come up with products and AI solutions where outcomes can be interpreted.
an alternative mechanism must be in place to audit AI system and ensure fundamental ethical policy for AI.
NON LINEAR MODEL IN AI:-


A non-linear model in AI is a statistical model that describes non-linear relationships between variables in experimental data. Non-linear models are often more powerful than linear models because they can capture more complex relationships.

Non-linear models can model the
growth of bacteria,
the decay of radioactive substances, or
the oscillation of a pendulum.

https://www.google.com/search?q=NON+LINEAR+MODEL+IN+AI&oq=NON+LINEAR+MODEL+IN+AI&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIICAEQABgWGB4yCAgCEAAYFhgeMg0IAxAAGIYDGIAEGIoFMg0IBBAAGIYDGIAEGIoFMg0IBRAAGIYDGIAEGIoFMg0IBhAAGIYDGIAEGIoFMgoIBxAAGIAEGKIEMgoICBAAGIAEGKIEMgoICRAAGIAEGKIE0gEJNjYwMmowajE1qAIIsAIB&sourceid=chrome&ie=UTF-8

INDUSTRIAL ADAPTABILITY : - AI had evolved beyond technology and had democratised knowledge to a wider range of people through the use of various applications. Explain / elaborate

Students must learn to adapt to new technology and equip themselves with artificial intelligence (AI) skills for industrial adaptability,

‘Empowering Students in the Age of AI: Skills for Tomorrow’s Innovators’

the core engineering subjects were leveraging AI tools now, it was essential for engineering professionals to focus on fundamental engineering skills, such as creative thinking and problem solving

AI skills could be a complementary tool and not a replacement.

whether AI has been incorporated in the curriculum of other disciplines, - Gen AI and design thinking had been included in the course curriculum of all the disciplines in good institutions

Students should also gain hands-on experience through various multi-disciplinary projects

Ethics and AI - about AI ethics training for students, had been interwoven into their curriculum, and that students were often questioned about the ethical interpretations of their projects.

focus towards contributing to sustainable development goals.

Gen AI tools were now used by both students and teachers,

INNOVATIVE, BUSINESS, LIFE STYLE : ‘Driving Innovation: AI’s Role in Transforming Business Operation’, - how businesses can integrate AI to enhance operational efficiency and drive innovation across functions ???
Artificial Intelligence (AI) will drive innovation and bring innovative thinking to life more effectively and efficiently,
the realm of business, it is going to revolutionise and deliver 100% results,
“There are three pillars: people, process, and technology.
Now there are many IT tools and systems that are being implemented by different industries and companies.
We need to look at the core areas where we have bottlenecks in the process, where we need to fine-tune our existing systems, and the need to migrate from the legacy to the digital journey,”.
For sustainability goals Speaking about how AI can contribute to achieving sustainability goals in business operations, such as reducing waste and optimising energy usage, products have come up with AI as the base.
“We need to have particular metrics to optimise our solutions.
Those can be applied to day-to-day activities and improvise the process by using technology to leverage their efficiency in operations,”
how AI is enabling companies to rethink traditional business models for greater confidence, when legacy companies want to become digital first, they should not just attempt to replace certain technologies with the latest ones.
There are certain questions that need to be asked on why the company wants to become digital firstand how much investment is required. All these should be implemented iteratively.
Impact on jobs On the likely impact of AI on jobs and the future of employability in the work place, - from an employee perspective, we need to get back to reality and embrace AI, and
from the organisation perspective, AI is not only a driver to save cost, it can also help in terms of making employees more efficient.
“Going forward, AI will do whatever it does best, right from processing and playing with massive amounts of data to solving complex problems.
Human intelligence and artificial intelligence will coexist, and they will complement each other,”
the key performance indicators that organisations should use to measure the success of AI initiatives, said optimisation of business, financial metrics, customer engagement and satisfaction, sustainability, and increasing productivity of the people are some of the key me trics.
“How are these tools going to enable our leadership and our teams on the ground to deliver more? In stead of having an army of people, how can we get better outcomes from the same people is an important metric,”
AI is going to make life better. “We need to embrace the new revolution,”
higher cost of customer services at the level of hyper-personalisation, :
“With AI, it is just a fraction of the cost on scale to look at it… People were scared it was going to take jobs. But actually, it gave more jobs. AI is going to increase opportunities.”
implementing AI in legacy systems and traditional business practices, observed that there is nothing called ‘legacy systems’ any more. “Because today, systems are capable of crunching structured and unstructured data,” .
the need to break the legacy mindset to adopt technologies, and said that motivation should be the prime driver behind digital transformation in an organisation
ETHICAL CONSIDERATIONS : ‘Transition from Hope to Reality: Navigating AI Challenges’

While artificial intelligence (AI) has made significant strides in transforming industries and improving efficiency, there are areas where human intervention remains essential —

GenAI had creep into all fields.

Today, it has taken centre stage in the education sector and cine industry,” “There is a general conception that GenAI can do everything — it cannot do everything. Giving the right input and the right data matters,”.

human skill is needed to review whether we are on the right track.

specialists required to handle operations and manage AI. -“GenAI is not just a simple programme. user need to consider the data, the security, and what gateway user is going to use,”

“user need a domain specialist, a data scientist to manage the data, a soft ware guy to integrate AI with the system,

digitisation is often confused with AI. -“The resource required for digitisation is far lower than AI,”

GenAI was growing fast. “To cope with those changes, we have been up skilling students and faculty,”

REPLACEMENT AS HUMAN CAPITAL

AI is augmentative tech, not a replacement for human capital:

artificial intelligence (AI) is “augmentative technology rather than a replacement for human capital.” “This is a vital period in our evolution as a country where, now and for the next 20 years, India will be the largest source of working-age human capital in the world.
This is our chance to take AI as a wonderful opportunity rather than to see it as a threat.” the volume of data collected, stored and available for analysis is “mind-boggling”. “
The first PCI in Madurai in 1981, had a RAM of 64 kilobytes and a hard drive of 20 me gabytes.
Today, we have run out of zeros to talk about the amount of data being generated every day.
Earlier, data was manually entered into a computer. “and Now, we have data that nobody has ever touched, coming in at such high volumes. This lends it self to the notion that we don’t need a human being in between.
The collection and storage is automatic.
The algorithms will process the data, and the results will come without any human being having touched it.
So, data is the first big thing that has changed.” we had moved past traditional notions of data and have taken a more inclusive approach, especially in the case of voice data, which according to him would be a gamechanger in India.
“If you have a huge volume of data and a large amount of processing capability, the physical infrastructure be comes the bottleneck.
The first question is do we have data centres that can store that kind of data.”the shift to wards automation and processing was inevitable.
“But at this point, technology still is augmentative.
We can see so many flaws, and limitations in technology.
It will take time for us to clean all this data and use it effectively.”
ultimate benefit of AI would be to address problems in governance.
Across the world, all governments had under-invested in infrastructure, processing capability, and cybersecurity.
job replacements would happen, but not immediately. “We have time and all of us collectively — the government, industry, academia, global companies, and innovators — will find a way to see this as an infection point, not just in technology, but in our economy.

FOR CLEAN DATA

‘AI can be an effective tool if availability of clean data is ensured’

Data is like oxygen and for artificial intelligence (AI) to be useful, one needs “oxygenated data”, the “clean data” that is available with a company,
‘AI in Decision Making: Enhancing Data Driven Strategies’, “Data plays a major role.
When a manufacturing company can have a battalion of people to check vehicle quality, I think it is the right time that every organisation also had a couple of people to check that the quality of data coming is also correct.”
Stating that AI is still a co-pilot, “AI can make a decision with an empathetic view” remains to be answered. “
ex- a person in an interior village who runs a door-to-door beauty parlour set up [after] seeking a loan in the microfinance industry. She was denied the loan by AI be cause her credit exposure is high, but a salesperson said that she was a good customer and has scope to expand and that she would also be able to repay the loan. The empathy angle is missed,”
AI will not replace human touch.
“wouldn’t worry too much about the quality of the data as a major stumbling block”.

FOR KIDS AND THEIR FUTURE

The younger generation has immense potential to transform technology into available tool for themselves and the industry they work in,
academicians, are embracing artificial intelligence (AI), besides students who see their future in AI.
‘Empowering Future Talent: Leveraging AI for Student Upskilling’ with the Naan Mudhalvan Scheme, Tamil Nadu’s flagship skill development programme, and the key challenges faced by TNSDC in implementing it. the scheme focused on bridging the skill gap in curricula, providing industry-relevant training, and offering emerging technology skills to students.
Noting that digital divide and the availability of qualified trainers were the key challenges,-TNSDC collaborated with academic institutions and industries to bridge these gaps.
Some of the emerging technologies, like electric vehicles technology, did not have standardised textbooks,
challenge of communication skills, is a concern flagged by the industry despite the technical capabilities of students, language barrier may become a thing of the past with AI tools being customised in regional languages. The TNSDC has prioritised the combination of communication skills and soft skills as a two-credit programme in curriculum to enhance the skills.

EX- ‘T.N. govt. to set up centre of excellence with AI lab’

The Tamil Nadu government will set up a Centre of Excellence with an Artificial Intelligence (AI) lab

the State recently announced its AI mission, and they would speak to the ICT Academy and explore how AI could be built into academics.

ICT Academy is a not-forprofit, Government of India initiative that aims at training higher education teachers and students.

the impact of AI on specific sectors, “One sector that has totally transformed is how we consume information. If person search for anything on Google, it gives an AI over view.”

“One of the biggest issues is bias, such as algorithm based bias and basic cognitive bias.”

though AI had been around for several decades, it has now emerged in a new avatar. We need to understand its capabilities and explore its full potential, .

Challenges ahead- Tamil Nadu has always been ahead of the curve and has come out with policies pertaining to AI.

The real challenges lie in end-to-end infrastructure for IT for AI to freely scale.
Infrastructure for AI training it self, and it is not as easy as it appears. The cost of AI hardware is going to be so high.
Eventually, the hard ware cost will come down.”
AI is no longer a thing of the distant future; it is here and is shaping the way we live, work, and innovate. “
While some important voices have argued that the impact of AI on humanity is likely to be as fundamental as fire,
cautioned needed that, without the right guardrails, it could turn out to be an uncontrollable, raging wildfire,”
ex- A robot warmly greeted the guests upon arrival, offering a unique and innovative welcome experience at the any event.

HOE TO USE ARTIFICIAL INTELLIGENCE TO FIGHT AGAINST AI's DARK SIDE?

Like the saying goes, “Set a thief to catch a thief,” one can use Artificial Intelligence (AI) to combat AI,
“ChatGPT and Large Language Model (LLM) are increasing productivity levels.
But there is a dark side to LLMs too. There are similar platforms which are used to generate convincing phishing campaigns. You wont even have a suspicion that it is a phishing campaign,”
‘AI in Cybersecurity: Building Next-Generation Defences Against Emerging Threats.’
scenario today, digital has become the first touch point of every business.
There is a lot of emphasis and momentum on security and privacy.”
given the digitisation speed.. not every employee is going to be digitally aware.. so there are chances of phishing campaigns and people inadvertently enter their credentials online.
In such cases AI will help you take a stand — they see suspicious sites and alert you,
AI helps take the next big action, she said adding that it is important to monitor your sample set to see if there is any drift in data

LARGE LANGUAGE MODEL - IN THE CONTEXT OF GENERAIVE AI ( Gen AI) - it developed alongside advances in machine learning, machine learning models, algorithms, neural networks and the transformer models that provide the architecture for these AI systems.

REFERENCES /FURTHER READINGS

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