Artificial Intelligence

Introduction:

Artificial intelligence (AI) is a branch of computer science concerned with making computers mimic human-like intelligence. AI enables a machine to perceive and respond to its changing environment.

Potential of AI:

•To Boost India’s Economic Growth Rate by 1.3% and Add 1 trillion Dollars by 2035 to India’s Economy.

•Employment Generation: Large Young Population, Emergent Startup Ecosystem. 

Types of AI:

1.Narrow Intelligence (Weak AI): Refers to the ability of a computer system to perform a narrowly defined task better than a human can.

2.General Intelligence (Strong AI or Human Level AI): Refers to the ability of a computer system to outperform humans in any intellectual task

3.Super Intelligence: Refers to a computer system that would have the ability to outperform humans in almost every field, including scientific creativity, general wisdom and social skills

Benefits of AI:

1. Healthcare: Al driven diagnostic, Early detection, drug research and discovery.

2. Education: Automation of repetitive task, Practical using AR/VR, Counselling sessions, Evaluation etc.

3. Agriculture: Al enabled agricultural robotics, Predictive analysis, Al for intelligent spraying etc.

4. Manufacturing: Quality checks, Prediction of equipment failure, Inventory management, real time changes in supply chain management etc.

5. Energy: Al managed smart grids, Anti-theft technologies, Fault prediction, Energy efficient systems using Alexa, Google nest etc.

6. Financial services: Personalised Banking, Fraud detection, Process automation etc.

7. Law enforcement: Facial recognition, Speech recognition, Predictive analytics etc.

Challenges with AI

1. Adverse Impact on Society: Fear of transferring existing biases existing in society

2. Lack of Accountability and Transparency: Difficult to differentiate between AI taken decision and Human taken decision

3. Ethical Concerns: related to equality, justice, and human dignity might pop up.

4. Infringes Intellectual Property rights: Many artists have claimed that their artworks were indiscriminately recreated by the Al, to create its own image rendering.

5. Privacy Issues: The use of Al can raise concerns about the collection, storage, and use of personal data.

Initiatives taken in India

1. MeitY's Future Skills PRIME in collaboration with NASSCOM, for re-skilling/ up-skilling of IT professionals in 10 Emerging areas including Al.

2. National Strategy for Artificial Intelligence. 

3. India is founding member of the Global Partnership on Artificial Intelligence {GPAI).

4. National Programme on Responsible Use of Al for Youth.

5. 'National Al Portal', a repository of Al based initiatives.

6. Responsible Al for Social Empowerment {RAISE) in 2020.

7. Technology Innovation Hubs under National Mission on Interdisciplinary Cyber- Physical Systems (NM- ICPS).

Way Forward:

1. Establishing ethical principles and guidelines for the development and deployment of AI

2. Gradual and regulated access of information can be introduced to AI and critical information can be isolated

3. More collaborative and cooperative engagement with different stakeholders including government, industry, academia and civil society

4. Design and Training of AI models should be based on diverse and inclusive data to minimize biasness to ensure equitable outcomes

Conclusion:

While artificial intelligence is rapidly evolving and holds immense promise to reshape our lives and economies, careful consideration of its ethical and social impact is crucial to maximize its benefits and minimize potential downsides.

Generative Artificial Intelligence

1. These programs are a conversational AI language based on deep learning model built on the transformer architecture. Example include: OpenAI's, ChatGPT, Google’s BARD AI, DALL-E, Codex, GPT-3, GPT-4 etc.

2. It uses a deep neural network and is trained on corpus of text data from the internet, allowing it to generate human-like text and to perform various tasks like question answering, and conversation

3. There are speculations that these platforms can replace Google search and more so humans in the future.

AI Benefit in Health

1. Prediction based Diagnosis – Faster, More Accurate Diagnosis and Prompt Detection of conditions such as stroke, pneumonia, breast cancer.

2. Drug Discovery and Development: Eg. Finding new antibiotic against superbug A. baumannii

3. Improving efficiency in Operations: Data patterns can help healthcare organisations to make most of their data, assets and resources

4. Health systems management and planning: Optimisation of Medical Supply chain, Chatbots to do repetitive tasks

5. Public Health Surveillance: Improve Identification of disease outbreaks and support surveillance

Challenges:

1. Data Privacy and Security: Huge amount of data regarding patient health care records

2. Biased AI Systems

3. Lack of Regulations: May not meet standards of scientific validity and accuracy

4. Ethical Concerns: Might give rise to Stigmatization of Individuals

5. Lack of Skilled Personnel: Not enough trained professionals will lead to bottleneck in realising maximum benefits

Conclusion:

The data collected by healthcare industry is enormous, such as health records, images, population data, claims data, clinical trial data, epidemiological data and mortality data. AI in this case can be a game changer in identifying correlations between various data sets and uncover pattern and insights that humans could never find on their own.

Therefore, judicious and regulated use of this data can be very beneficial for the human civilisation and improving human capital which will prove beneficial for the economic growth of country in the long run.

AI Benefit in Agriculture:

1. Intelligent Crop Planning: Eg. Credit Planning, Micro-Irrigation, Inputs Planning, Sowing Windows, Potential etc.

2. Smart and Precision Farming: Mechanisation of Farms, Wearable Sensors, Pest Prediction, Irrigation, Weather Advisory etc.

3. Farmgate to Fork: Quality & Traceability, Supply Chain Optimisation, Demand Prediction, Warehouse Management

4. AI Based Surveillance Systems: Real Time Field Monitoring, Boundary Monitoring

5. Efficient Labour: Robots for harvesting, sowing, removing weeds etc.

Challenges

1. Lack of Datasets: No historical data

2. High Investment Costs

3. Handling of Massive Data

4. Bridging the gap between Farmers and AI Engineers: Lab and Farm unconnected

5. Lack of Technical Knowhow and Awareness

6. Marginalisation, Poor Internet Penetration Rates and Digital Divide

Conclusion

AI helps farmers not just in automating their agricultural operations but also changes how agriculture is done based on data and knowledge. This enables precision cultivation for improved crop output and quality while using less resources.

Author: Arjun Kr. Paul, Faculty