What’s the news?

• The rapid growth of neurotechnology, driven by advances in neuroscience and technology, has given rise to a field with immense potential and profound ethical implications.

Central Idea

• Neurotechnology encompasses various aspects, from Brain-Computer Interfaces (BCIs) to neuroimaging and neurostimulation. As this field expands, it poses challenges to human privacy, autonomy, and dignity. In this context, the need for ethical guidelines and governance becomes paramount.

What is neurotechnology?

• Neurotechnology is a multidisciplinary field that combines neuroscience, engineering, and technology to study, interact with, and manipulate the human nervous system, particularly the brain and its functions.
• It involves the development and application of various techniques, tools, and devices to better understand and interface with the brain and nervous system.

What is neurowarfare?

• Neurowarfare, also known as neurotechnology warfare, refers to the use of advanced neurotechnological tools, techniques, and agents in military operations and conflicts.
• It represents the convergence of neuroscience, neurotechnology, and warfare strategies, with the aim of gaining a tactical or strategic advantage on the battlefield or in intelligence operations.
• Neurowarfare explores the manipulation of the human nervous system, particularly the brain, for various purposes, both offensive and defensive.

The ethics of neurotechnology

• Brain-Computer Interfaces (BCIs) and Brain-Machine Interfaces (BMIs): BCIs offer direct communication between the brain and external devices, while BMIs integrate neural signals with machines for various applications, including prosthetics and exoskeletons. Ethical concerns arise regarding privacy, autonomy, and mental influence.
• Neuroimaging and Neurostimulation: Neuroimaging provides access to neurological data, while neurostimulation modulates neural activity for therapeutic purposes. The potential for behavioral changes and privacy invasion necessitates regulation.
• Gathering and Use of Neurological Data: The absence of guidelines for gathering, studying, and using neurological data requires immediate attention, especially in light of private sector developments such as Neuralink’s brain implant chip.

Neurowarfare: The Emerging Threat

• Neurotechnological Agents: Advances in synthetic biology open doors to neurotechnological agents that can impact neurological abilities. This includes neuropharmacological agents like amphetamines and neurotechnological devices.
• Dual-Use Nature: Neurotechnology can have dual-use applications, both civilian and military. Neurowarfare refers to its use in military operations, potentially enhancing soldiers’ cognitive abilities or disrupting the cognitive functions of adversaries.
• Case Study: Havana Syndrome: The mysterious Havana Syndrome experienced by US intelligence personnel raises concerns about directed energy weapons and intentional attacks. Similar cases have been reported in Guangzhou, China.

Ethical Concerns in Neurowarfare

• Informed Consent and Privacy: Ethical use of neurotechnology in warfare requires informed consent for soldiers and civilians. Oversight and restrictions on using such innovations for harm are essential.
• Psychological Harm: Studying the psychological impact of neurotechnology weapons is imperative to establishing limits on their deployment.
• Protection of Non-Combatants: Civilians must be shielded from neurotechnology applications, ensuring their privacy, consent, and protection from manipulation.

Importance of International Cooperation and Responsible Governance

• International Cooperation: Organizations like the OECD and UNESCO have initiated ethical guidelines for neurotechnology. However, global governance must extend to neurowarfare, with disarmament forums incorporating ethical oversight and transparency.
• Accountability: State actors should be held accountable through reporting systems, ensuring responsible research and the use of neurotechnology in warfare.

Conclusion

• Neurotechnology holds immense potential for human advancement but also raises profound ethical challenges in the context of neurowarfare. Striking a balance between technological progress and ethical considerations is crucial to safeguarding human rights and global security in the age of neurotechnology.

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Implantable Brain-Computer Interface

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Central Idea

• In a significant breakthrough within the field of quantum computing, researchers from the National Energy Technology Laboratory (NETL) and the University of Kentucky have developed an algorithm that holds great promise for advancing carbon capture technology. This cutting-edge algorithm, which can be implemented on existing quantum computers, has the potential to revolutionize the reduction of carbon emissions.

Global Warming: A Pressing Concern

• Global warming has emerged as a pressing concern for humanity, primarily caused by the escalating levels of carbon dioxide (CO2) in the atmosphere resulting from extensive fossil fuel consumption.
• Atmospheric CO2 has risen by nearly 50 percent from pre-industrial levels, and recent data from the National Oceanic and Atmospheric Administration reveals a steady increase in global surface average CO2 levels.
• To counteract global warming, one approach is atmospheric carbon capture, wherein specific compounds, such as amines like ammonia (NH3), are used to chemically bind with CO2 and remove it from the atmosphere. However, current carbon capture reactions tend to be expensive and inefficient.

Role of Quantum Computing in Carbon Capture

• Simulating Molecular Interactions: Quantum computers have the capability to simulate and analyze the molecular interactions involved in carbon capture reactions at a quantum scale. Classical computers are limited in their ability to handle such complex calculations, whereas quantum computers excel in solving quantum mechanical problems.
• Optimization of Carbon Capture Reactions: Quantum computing algorithms, such as the Variational Quantum Eigensolver (VQE), can be used to optimize and improve the efficiency of carbon capture reactions. By leveraging the power of quantum computers, researchers can find optimal conditions and compounds that enhance the effectiveness of capturing carbon dioxide from the atmosphere.
• Overcoming Computational Challenges: Quantum computers can overcome computational challenges that hinder classical computers in simulating and predicting the behavior of molecules. These challenges include the exponential scaling of computational resources required for larger and more complex molecules. Quantum algorithms provide a more efficient approach to solving such problems.
• Accelerating Research and Development: Quantum computing speeds up the research and development process in carbon capture technology by drastically reducing the time required for complex calculations. Quantum computers can explore a vast number of potential solutions and configurations, enabling researchers to identify effective carbon capture methods more quickly.
• Quantum Chemistry Applications: Quantum computing has broader applications in quantum chemistry, enabling the study of various chemical reactions beyond carbon capture. This opens up possibilities for advancements in fields such as biology, medicine, and materials science, where understanding molecular interactions is critical.
• Future Potential: As quantum computing technology continues to evolve and mature, it holds the potential to revolutionize carbon capture by addressing challenges such as limited qubits and noise in quantum algorithms. Continued research and investment in quantum computing will likely lead to more efficient and practical solutions for carbon capture in the future.

India Leveraging quantum Computing Technology to Combat Global Warming

• Carbon Emission Reduction: India is one of the largest contributors to global carbon emissions. By investing in quantum computing technology, India can accelerate the development and implementation of advanced carbon capture methods, leading to a significant reduction in carbon emissions.
• Renewable Energy Optimization: Quantum computing can be utilized to optimize the deployment and management of renewable energy sources, such as solar and wind farms. Quantum algorithms can analyze complex energy data and optimize energy generation and distribution systems, maximizing the efficiency and effectiveness of renewable energy solutions.
• Policy and Planning: Quantum computing can aid in developing sophisticated models and simulations for climate change policy and planning. It can assist policymakers in assessing the impact of various interventions, optimizing resource allocation, and devising effective strategies to mitigate climate change.
• Scientific Research and Collaboration: Quantum computing fosters collaboration between Indian scientific institutions, universities, and international organizations. India can collaborate with leading research institutions to advance quantum computing applications in climate science, carbon capture, and other related fields. This collaboration enables knowledge exchange, enhances research capabilities, and drives innovation.
• Technological Advancement: Quantum computing requires advanced infrastructure and research facilities. By investing in quantum technology, India can develop its technological capabilities, attract top talent, and foster innovation in related industries. This, in turn, can contribute to India’s overall technological advancement and competitiveness on the global stage.
• Economic Opportunities: Quantum computing has the potential to create new industries and business opportunities. By investing in quantum technology, India can position itself as a hub for quantum computing research and development, attracting investment and fostering a quantum technology ecosystem. This can lead to job creation, economic growth, and technological leadership in the field of quantum computing.
• Sustainable Development Goals: Combating global warming aligns with India’s commitment to achieving the United Nations’ Sustainable Development Goals (SDGs). Quantum computing can support various SDGs, including affordable and clean energy (SDG 7), climate action (SDG 13), and partnerships for the goals (SDG 17), by providing innovative solutions to address climate change challenges.

Potential challenges in India’s Efforts to Leverage Quantum Computing

• Technology Readiness: Quantum computing is still an emerging technology, and practical implementations for carbon capture and other climate-related applications are in the early stages. The development of quantum computers with sufficient qubits, stability, and error correction capabilities may take time, and it is uncertain when these technologies will become mature enough for widespread use.
• Research and Development Funding: Quantum computing research and development require substantial investments in infrastructure, talent, and equipment. Ensuring adequate funding for quantum research, including building and maintaining quantum computing facilities, can be a challenge.
• Skilled Workforce: Quantum computing is a highly specialized field that requires expertise in quantum physics, computer science, and algorithms. Developing a skilled workforce capable of working with quantum technologies is essential.
• Infrastructure and Access: Quantum computing infrastructure, including quantum computers and supporting technologies, is limited. Ensuring widespread access to quantum computing resources, particularly for researchers and scientists working on climate-related challenges, may pose logistical and resource challenges.
• Integration with Existing Systems: Integrating quantum computing technologies into existing computational and data analysis systems can be complex. Developing compatible software and algorithms that can effectively utilize quantum computers while seamlessly integrating with classical computing infrastructure is a significant challenge.
• Ethical and Policy Considerations: As quantum computing evolves, ethical and policy considerations surrounding its applications in carbon capture and climate-related research need to be addressed.

Way Forward

• Increased Funding: The Indian government should allocate significant funding for quantum computing research and development, specifically focusing on applications related to carbon capture and climate change.
• Collaboration and Partnerships: Collaborate with leading international research institutions, universities, and industry partners to leverage their expertise, resources, and infrastructure.
• Skill Development: Invest in educational programs, training initiatives, and scholarships to develop a skilled workforce in quantum computing. Foster collaboration between academic institutions, research organizations, and industry to create a talent pipeline of quantum computing experts.
• Quantum Computing Infrastructure: Develop and expand quantum computing infrastructure within India. This includes building quantum computing facilities, increasing the availability of quantum computers, and providing access to quantum resources for researchers and scientists working on climate-related challenges.
• Quantum Algorithms and Software Development: Support the research and development of quantum algorithms and software specifically tailored for carbon capture and climate modeling. This involves optimizing quantum algorithms for efficiency, developing algorithms for simulating molecular interactions, and integrating quantum computing with classical computing systems.
• Policy Framework: Establish a policy framework that addresses the ethical, legal, and regulatory aspects of quantum computing in carbon capture and climate change applications. This framework should consider issues such as data privacy, security, intellectual property rights, and responsible use of quantum technologies.

Conclusion

• Quantum computing’s potential to transform carbon capture technology is a significant development in the fight against global warming. The algorithm devised by the NETL-Kentucky team demonstrates the power of combining quantum and classical computing to address complex challenges. India, as a major contributor to carbon emissions, should prioritize investment in quantum computing to accelerate the reduction of its carbon footprint.

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Central Idea

• In the realm of technological advancements, certain breakthroughs possess the power to revolutionize entire industries. Artificial Intelligence (AI) for software, quantum computing for computers, and graphene for materials are such game-changers. While India has made commendable progress in AI and shows promise in quantum computing, it is crucial for the country to catch up in the domain of graphene.

What is Graphene?

• Graphene is a single layer of carbon atoms arranged in a hexagonal lattice pattern. It is a two-dimensional material that is incredibly thin, strong, and lightweight. In fact, it is the thinnest material known to date, with a thickness of just one atom.
• Despite its thinness, graphene is remarkably strong, around 200 times stronger than steel, yet incredibly flexible.

Why Graphene is known as The Wonder Material?

• Exceptional Strength: Despite being only one atom thick, graphene is incredibly strong. It is approximately 200 times stronger than steel, yet it is incredibly flexible. This combination of strength and flexibility makes it highly desirable for applications where strength and durability are crucial.
• Superb Electrical Conductivity: Graphene is an excellent conductor of electricity, even surpassing traditional conductors like copper. It allows the flow of electrons with minimal resistance, making it ideal for developing high-performance electronics and electrical devices.
• High Thermal Conductivity: Along with its electrical conductivity, graphene also exhibits excellent thermal conductivity. It can efficiently transfer heat, making it valuable for applications requiring efficient heat management, such as in electronics, thermal management systems, and energy storage devices.
• Transparency: Graphene is nearly transparent and can absorb only 2% of light passing through it. This property makes it an intriguing material for optoelectronic devices, transparent conductive films, and touchscreens, as it enables the transmission of light while maintaining conductivity.
• Impermeability to Gases: Graphene is impermeable to gases, even those as small as hydrogen and helium. This property opens up possibilities for applications in gas separation, filtration, and storage, as well as creating barriers against moisture or gas permeation in various industries.
• Versatility and Composite Formation: Graphene can be combined with other materials to create composite materials with enhanced properties. Even in small quantities, graphene can significantly improve the strength, conductivity, and other characteristics of composite materials. This versatility expands its potential applications in fields such as aerospace, automotive, construction, and sports equipment.
• Wide Range of Applications: Graphene has the potential to revolutionize numerous industries and sectors. It can be used in energy storage devices like batteries and supercapacitors, for developing sensors, inks, membranes for water purification, and in healthcare for drug delivery systems and biosensors. Its applications also extend to areas such as defense and aerospace, where its exceptional strength, conductivity, and sensitivity to environmental changes offer unique advantages.

Global Graphene Landscape

• China: China declared graphene a priority in its 13th Plan. China has emerged as a global leader in the production and commercialization of graphene. China’s emphasis on graphene is evident from its graphene-related patent filings, which have surpassed those of other leading nations in recent years.
• United States: The United States has a strong presence in the graphene landscape, with active research and development initiatives. Several universities, research institutions, and companies in the U.S. are at the forefront of graphene research, exploring its potential applications and commercialization prospects. The country has a considerable number of graphene-related patents and is home to leading graphene companies and startups.
• United Kingdom: The UK has been a pioneer in graphene research since its discovery. The University of Manchester, where graphene was first isolated, remains a hub for graphene research and innovation. The UK government has invested in the National Graphene Institute and the Graphene Engineering Innovation Centre to support research and development in graphene applications.
• South Korea: South Korea has active research programs, industry collaborations, and graphene-related patent filings. South Korean companies are involved in graphene production, commercialization, and application development across various sectors.
• Japan: Japan has a significant presence in graphene research and commercialization. Japanese universities and research institutions have made notable contributions to the field. The country has a strong focus on developing graphene-based technologies in areas such as electronics, energy storage, and composite materials. Japanese companies are actively involved in graphene production and application development.
• Russia: Russia has a growing presence in the graphene landscape, with notable research activities and patents in the field. Russian universities and research institutes are engaged in graphene research, and the country has witnessed the establishment of graphene-focused companies.
• Singapore: Singapore has invested in graphene research and development, aiming to position itself as a regional hub for graphene-related technologies. The country has established research institutes and centers focused on graphene and has attracted collaborations with international partners.

India’s progress in the graphene sector

• Research and Academic Contributions: The Centre for Nano Science and Engineering at the Indian Institute of Science (IISc) Bangalore, in collaboration with KAS Tech, has been actively involved in graphene research and development.
• Start-ups and Industry Initiatives: Several start-ups and foreign subsidiaries have emerged in India, focusing on graphene or graphene derivatives. Notably, Tata Steel has achieved success in growing graphene using annealing and extracting atomic carbon from steel surfaces. They have also explored the use of graphene in recycling plastic products. Other start-ups, such as Log 9 and RF Nanocomposites, have patented graphene-based technologies for ultracapacitors, EMI shielding, and stealth applications, respectively.
• Graphene Innovation Centre in Kerala: In a laudable step, the India Innovation Centre for Graphene was established in Kerala. This center, implemented by the Digital University Kerala in partnership with Tata Steel and C-MET, Thrissur, aims to foster large-scale innovation activity around graphene. It serves as a collaborative platform for research, development, and commercialization of graphene-based technologies.
• Patents and Intellectual Property: While India’s graphene-related patent filings are relatively modest compared to other leading countries, there have been efforts to secure intellectual property. Indian researchers and institutions have filed patents for graphene-based technologies and applications, demonstrating innovation and progress in the field.

Facts for prelims: Semiconductors

Way Ahead: India’s graphene sector

• National Graphene Mission: Establish a dedicated National Graphene Mission, similar to initiatives undertaken by other countries. This mission should focus on fostering research, development, and commercialization of graphene-based technologies, with clear objectives, timelines, and allocated resources.
• Increased Research and Development: Encourage and fund research and development activities in graphene across academic institutions, research organizations, and industry. Foster collaborations between academia, industry, and government to drive innovation and accelerate the discovery of new applications for graphene.
• Infrastructure and Facilities: Invest in infrastructure and facilities for large-scale production, characterization, and testing of graphene. Develop advanced laboratories equipped with state-of-the-art instruments to support graphene research and development.
• Skill Development and Training: Promote skill development programs and training initiatives to build a skilled workforce with expertise in graphene technology. Develop specialized courses and training modules at educational institutions to produce a talent pool proficient in graphene research, fabrication, characterization, and application development.
• Industry-Academia Collaboration: Foster stronger collaboration between industry and academia to bridge the gap between research and commercialization. Encourage joint research projects, technology transfer, and the establishment of industry-academia consortia focused on graphene.
• Funding and Financial Support: Increase funding for graphene research and development through government grants, industry investments, and venture capital. Provide financial support and incentives for start-ups and companies working on graphene technologies to encourage entrepreneurship and product development.
• Intellectual Property Protection: Strengthen intellectual property protection mechanisms and encourage researchers and companies to file patents for graphene-based technologies and applications. Support the development of patent pools and licensing frameworks to facilitate technology transfer and commercialization.

Conclusion

• The potential of graphene to transform industries cannot be understated. As the world advances towards the graphene age, India must secure its position as a leader rather than a bystander. The time to prioritize graphene is now, as the production of high-grade graphene may become concentrated in select global locations, similar to semiconductors. India has witnessed the consequences of missing out on the semiconductor wave, and it cannot afford to repeat history.

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Central Idea

• Artificial Intelligence (AI) has gained worldwide attention, and many mature democracies are using it for better legislative procedures. In India, AI can be used to assist parliamentarians in preparing responses for legislators, enhancing research quality, and obtaining information about any Bill, legislative drafting, amendments, interventions, and more. However, before AI can work in India, there is a need to codify the country’s laws, which are opaque, complex, and face a huge translation gap between law-making, law-implementing, and law-interpreting organizations.

What is Artificial Intelligence?

• AI is a constellation of technologies that enable machines to act with higher levels of intelligence and emulate the human capabilities of sense, comprehend and act.
• The natural language processing and inference engines can enable AI systems to analyze and understand the information collected.
• An AI system can also take action through technologies such as expert systems and inference engines or undertake actions in the physical world.
• These human-like capabilities are augmented by the ability to learn from experience and keep adapting over time.
• AI systems are finding ever-wider application to supplement these capabilities across various sectors

Need to Codify Laws

• Current laws are complex and opaque: Current laws in India pose many challenges, such as their complexity, opaqueness, and lack of a single source of truth.
• The India Code portal does not provide complete information: The India Code portal is not enough to provide complete information about parent Acts, subordinate legislation, and amendment notifications.
• AI can be used to provide comprehensive information: There is a need to make laws machine-consumable with a central law engine, which can be a single source of truth for all acts, subordinate pieces of legislation, gazettes, compliances, and regulations. AI can use this engine to provide information on applicable acts and compliances for entrepreneurs or recommend eligible welfare schemes for citizens.

Assisting Legislators

• Potential of AI for legislators: AI can help Indian parliamentarians manage constituencies with a huge population by analysing citizens’ grievances and social media responses, flagging issues that need immediate attention and assisting in seeking citizen inputs for public consultation of laws and preparing a manifesto.
• AI-powered assistance: Many Parliaments worldwide are now experimenting with AI-powered assistants.
• For instance:
• Netherlands’s Speech2Write system: The Speech2Write system in the Netherlands House of Representatives, which converts voice to text and translates voice into written reports.
• AI tools Japan: Japan’s AI tool assists in preparing responses for its legislature and helps in selecting relevant highlights in parliamentary debates.
• Brazil: Brazil has developed an AI system called Ulysses, which supports transparency and citizen participation.
• NeVA portal India: India is also innovating and working towards making parliamentary activities digital through the ‘One Nation, One Application’ and the National e-Vidhan (NeVA) portal.

Simulating Potential Effects of Laws

• Dataset modelling: AI can simulate the potential effects of laws by modelling various datasets such as the Census, data on household consumption, taxpayers, beneficiaries from various schemes, and public infrastructure.
• Flag outdated laws: In that case, AI can uncover potential outcomes of a policy and flag outdated laws that require amendment.
• For example: During the COVID-19 pandemic, ‘The Epidemic Diseases Act, 1897’ failed to address the situation when the virus overwhelmed the country. Several provisions in the Indian Penal Code (IPC) are controversial and redundant, such as Article 309 (attempted suicide) of the IPC continues to be a criminal offense. Many criminal legislation pieces enacted more than 100 years ago are of hardly any use today.

Conclusion

• The COVID-19 pandemic has given a strong thrust to the Digital India initiative, and a digitization of services needs to be kept up in the field of law, policy-making, and parliamentary activities, harnessing the power of AI. However, the use of AI must be encouraged in an open, transparent, and citizen-friendly manner, as AI is a means to an end, not an end in itself. Therefore, it is necessary to address the current challenges faced by India’s laws before AI can be effectively used to assist parliamentarians in their legislative duties.

Mains Question

Q. Artificial Intelligence (AI) has gained worldwide attention, and many mature democracies are using it for better legislative procedures. In this light evaluate the potential of AI in assisting Indian parliamentarians.

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Central Idea

• OpenAI’s GPT-4, the latest AI model, is creating shock waves around the world. It has incredible capabilities, but also raises ethical questions and concerns about its potential misuse.

Capabilities of GPT-4

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Context

• With the launch of Open AI’s ChatGPT late last year, the impending changes in the nature of work, creativity and economy as a whole have moved from being the subject of futuristic jargon to an immediate challenge.

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Background

• Since at least 2015 when Klaus Schwab popularised the term Fourth Industrial Revolution at that year’s World Economic Forum terms like 4IR, Artificial Intelligence (AI), Internet of Things, Future of Work, entered the lexicon of politicians, bureaucrats, consultants and policy analysts.

Sample developments over just the last few days

• A judge in Colombia included his conversations with ChatGPT in a ruling;
• Microsoft is integrating the bot with its search engine, Bing, and other products;
• Google is reportedly trying to launch a similar tool and there are reports that ChatGPT can already code at entry level for Google engineers.

What are the Concerns?

• Lifestyle may become redundant: Concerns about plagiarism in universities and beyond, as well as the fear that many white-collar jobs may become redundant in the coming years, as AI becomes more ubiquitous and sophisticated.
• Implications on labour, education and authenticity: The AI revolution is likely to have serious implications on labour, education, authenticity of content and its authorship, and much else.
• Case of Social media’s influence in US elections: The concerns around social media’s influence on politics and society became sharp in the aftermath of the 2016 US presidential elections and accusations of voter manipulation by foreign agents. Much of the world is still struggling with the questions raised then.

Do you what exactly ChatGPT is?

• Simple definition: ChatGPT is a chatbot built on a large-scale transformer-based language model that is trained on a diverse dataset of text and is capable of generating human-like responses to prompts.
• A human like language model: It is based on GPT-3.5, a language model that uses deep learning to produce human-like text.
• It is more engaging with details: However, while the older GPT-3 model only took text prompts and tried to continue on that with its own generated text, ChatGPT is more engaging. It’s much better at generating detailed text and can even come up with poems.
• Keeps the memory of the conversations: Another unique characteristic is memory. The bot can remember earlier comments in a conversation and recount them to the user.
• Human- like resemblance: A conversation with ChatGPT is like talking to a computer, a smart one, which appears to have some semblance of human-like intelligence.

Anticipating possible futures requires engagement with the opportunities

• The Struggle to keep up with technology in policymaking:

1. Governments worldwide face a challenge in creating policies that keep up with the rapid pace of technological advancement.
2. Policymakers should understand that they must work to bridge the gap between technology and regulation, as a growing divide could lead to problems.

• Preparing for technological change in education and workforce:

1. In addition to creating regulations that support innovation, it’s crucial to plan for the changes that new technology will bring to education and employment.
2. This includes anticipating new job types and skills required, as well as updating the education system to prepare future workers.

• Importance of Preparing for technological change for India:

1. India has been facing the challenge of balancing privacy and regulation in the handling of data for several years.
2. Successfully adapting to technological changes is crucial for India to make the most of its large, young workforce. If not addressed in time, the consequences could be severe

Conclusion

• The transformations the new technology is bound to bring about must be met with swift adjustments in the broader national and international legal and policy architecture. The lag between technology innovation and policy that was seen with the rise of Big Data and social media can serve as a lesson.

Mains Question

Q. With the rapid innovations and launching of Artificial intelligence models everyday will change the nature of work, creativity and economy as a whole. comment

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Context

• Around the end of last year, social media spaces were trending with Lensa-generated images of online users. A subscription app, Lensa, makes graphic portraits, called “Magic Avatar” images, using selfies uploaded by its users. As AI takes a strong foothold over the realm of art, are we equipped with mechanisms to define what is right and what is wrong in this domain in the first place?

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The case of Lensa app

• A subscription app, Lensa, makes graphic portraits, called Magic Avatar images, using selfies uploaded by its users.
• Celebrities worldwide stepped in to show how they looked so perfect in their avatars in a Lensa world.
• However, a few days later, hundreds of women netizens worldwide started flagging issues with their avatars. They pointed out how their avatar images had their waists snatched and showed sultry poses.
• Even after these women uploaded different pictures, Lensa generated hyper-sexualised, semi-pornographic images.

How art is generated using Artificial Intelligence?

• Uses algorithms based on textual prompts: AI art is any art form generated using Artificial Intelligence. It uses algorithms that learn a specific aesthetic based on textual prompts and, after that, go through vast amounts of data in the form of available images as the first step.
• Algorithms generate new images: In the next step, the algorithm tries to generate new images that tally with the kind of aesthetics that it has learnt.
• Role of artists with right keystrokes: The artist becomes more like a curator who inputs the right prompt to develop an aesthetically-fulfilling output. While artists use brush strokes in other digital platforms like Adobe Photoshop, in programmess like Dall-E and Midjourney, all it takes are keystrokes.
• For example: The generation of an artwork like Starry Night in the digital era. While Van Gogh would have taken days of effort to conceptualise and get the correct strokes and paint, in the AI art era, it is just a matter of the right textual prompts.

Can it truly capture the essence of humanity?

• The impact of AI-generation on the masses’ experience of art: Art is one of the few pursuits that makes life meaningful. It remains to be seen if AI-generated art will alienate the experience of art from the masses.
• AI takes away the satisfaction of creating artworks: AI-generated art dehumanises artworks. Perhaps the most satisfying aspect of generating an artwork lies in making it.
• The questions over the capability of AI to capture subtle human emotions: It is also doubtful whether AI art will capture the most subtle of human emotions. How much humour is “humorous” for AI? Can AI express grief and pain in the most profound ways as described by our poets? Can AI capture the enigmatic smile of Mona Lisa that makes one believe that she is shrouded in mystery?

Have you heard about Midjourney?

• Midjourney is an AI based art generator that has been created to explore new mediums of thought.
• It is an interactive bot, which uses machine learning (ML) to create images based on texts. This AI system utilises the concepts and tries to convert them into visual reality.
• It is quite similar to other technologies such as DALL-E 2.

Arguments in favor of such art

• Thatre D opera Spatial generated by Midjourney: The question of whether AI art is causing “a death of artistry” was raised, last year, when an entry called “Théâtre D’opéra Spatial” generated from Midjourney (an artificial intelligence programme) by Jason M Allen won the Blue Ribbon at the Colorado State Fair.
• Finding suitable prompts is no less than a genius art: AI artists like Allen think finding suitable prompts to create an artwork amounts to creativity and qualifies AI art as genuine or authentic.
• AI could democratise art world: Some artists believe AI art could democratise the art world by removing gatekeepers.

Concerns over the biases in data

• There is bias in this data available for AI inputs due to a lack of representation of the less privileged communities’ women, people of colour and other marginalised groups.
• Most of the training data for AI art currently emerges in the Global North and is often mired by the stereotypes of ableism, racism and sexism.
• Historically, art has performed a political function as a venue for dissent. Can AI art overcome these inherent biases in data to bring out meaningful political engagement?

Conclusion

• AI-generated art can bring new ideas and possibilities to the art world, but it is important to think about how it might change people’s experience of art and if it takes away the human touch. It is also important to question if AI can truly capture the emotions that make art so special. It’s best to approach AI-generated art with an open mind and consider both the good and bad.

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Context

• 2022 had an unusual blue-ribbon winner for emerging digital artists; Jason Allen’s winning work Théâtre D’opéra Spatial was created with an AI Generative model called Midjourney.

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What is Midjourney?

• Midjourney is an AI based art generator that has been created to explore new mediums of thought.
• It is an interactive bot, which uses machine learning (ML) to create images based on texts. This AI system utilises the concepts and tries to convert them into visual reality.
• It is quite similar to other technologies such as DALL-E 2.

The journey of AI generative models so far

• Midjourney generator: Midjourney is one of the rash of AI-generated Transformer or Generative or Large Language Models (LLMs) which have exploded onto our world in the last few years.
• Earlier models: Models like BERT and Megatron (2019) were relatively small models, with up to 174 GB of dataset size, and passed under the collective public radar.
• Composition skills of GPT3: GPT3, released by OpenAI with a 570 GB dataset and 175bn parameters was the first one to capture the public consciousness with some amazing writing and composition skills.
• Models that creat images or videos based on texts: The real magic, however, started with Transformers which could create beautiful and realistic pieces of art with just a text prompt OpenAI’s DALL-E2, Google’s Imagen, the open-source Stable Diffusion and, obviously, Midjourney. Not to be left behind, Meta unleashed a transformer which could create videos from text prompts.
• ChatGPT, a latest and more evolved, like real communication: Recently in late 2022 came the transformer to rule them all ChatGPT built on GPT3, but with capabilities to have real conversations with human beings.

Are these models ethical?

• Ethics is too complex a subject to address in one short article. There are three big ethical questions on these models that humanity will have to address in short order.

1. Environmental: Most of the bad rap goes to crypto and blockchain, but the cloud and these AI models running on it take enormous amounts of energy. Training a large transformer model just once would have CO2 emissions equivalent to 125 roundtrips from New York to Beijing. This cloud is the hundreds of data centres that dot our planet, and they guzzle water and power at alarming rates.
2. Bias; as it do not understand meaning and its implications: The other thorny ethical issue is that sheer size does not guarantee diversity. Timnit Gebru was with Google when she co-wrote a seminal research paper calling these LLMs ‘stochastic parrots’, because, like parrots, they just repeated a senseless litany of words without understanding their meaning and implications.
3. Plagiarism, question of who owns the original content: The third prickly ethical issue, which also prompted the artist backlash to Allen’s award-winning work is that of plagiarism. If Stable Diffusion or DALL-E 2 did all the work of scouring the web and combining multiple images (a Pablo Picasso Mona Lisa, for example), who owns it. Currently, OpenAI has ownership of all images created with DALL-E, and their business model is to allow paid users to have rights to reproduce, paint, sell and merchandise images they create. This is a legal minefield the US Copyrights office recently refused to grant a copyright to a piece created by a generative AI called Creativity Machine, but South Africa and Australia have recently announced that AI can be considered an inventor.

Do you know ChatGPT?

• ChatGPT is a chatbot built on a large-scale transformer-based language model that is trained on a diverse dataset of text and is capable of generating human-like responses to prompts.
• A conversation with ChatGPT is like talking to a computer, a smart one, which appears to have some semblance of human-like intelligence.

What are the other concerns?

• Besides the legal quagmire, there is a bigger fear: This kind of cheap, mass-produced art could put artists, photographers, and graphic designers out of their jobs.
• Machine does not have human like sense: A machine is not necessarily creating art, it is crunching and manipulating data and it has no idea or sense of what and why it is doing so.
• As it is cheap, corporate might consider using it at a large scale: But it can do so cheaply, and at scale. Corporate customers might seriously consider it for their creative, advertising, and other needs.

Conclusion

• Legal and political leaders across the world are sounding the alarm about the ethics of large generative models, and for good reason. As these models become increasingly powerful in the hands of Big Tech, with their unlimited budgets, brains and computing power, these issues of bias, environmental damage and plagiarism will become even more fraught. Such AI models should not be used to create chaos rather a harmonious existence.

Mains question

Q. Name some of the models of AI based art generators. Discuss the ethical concerns of such models.

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Context

• Many of us are familiar with the concept of what a “chatbot” is and what it is supposed to do. But this year, OpenAI’s ChatGPT turned a simple experience into something entirely different. ChatGPT is being seen as a path-breaking example of an AI chatbot and what the technology could achieve when applied at scale.

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Background

• ChatGPT by OpenAI: Artificial Intelligence (AI) research company OpenAI on recently announced ChatGPT, a prototype dialogue-based AI chatbot capable of understanding natural language and responding in natural language.
• Will be able to implement in softwares soon: So far, OpenAI has only opened up the bot for evaluation and beta testing but API access is expected to follow next year. With API access, developers will be able to implement ChatGPT into their own software.
• Remarkable abilities: But even under its beta testing phase, ChatGPT’s abilities are already quite remarkable. Aside from amusing responses like the pumpkin one above, people are already finding real-world applications and use cases for the bot.

What is Chatbot?

• A chatbot (coined from the term “chat robot”) is a computer program that simulates human conversation either by voice or text communication, and is designed to help solve a problem.
• Organizations use chatbots to engage with customers alongside the classic customer service channels like phone, email, and social media.

What is ChatGPT?

• Simple definition: ChatGPT is a chatbot built on a large-scale transformer-based language model that is trained on a diverse dataset of text and is capable of generating human-like responses to prompts.
• A human like language model: It is based on GPT-3.5, a language model that uses deep learning to produce human-like text.
• It is more engaging with details: However, while the older GPT-3 model only took text prompts and tried to continue on that with its own generated text, ChatGPT is more engaging. It’s much better at generating detailed text and can even come up with poems.
• Keeps the memory of the conversations: Another unique characteristic is memory. The bot can remember earlier comments in a conversation and recount them to the user.
• Human- like resemblance: A conversation with ChatGPT is like talking to a computer, a smart one, which appears to have some semblance of human-like intelligence.

The Question arises: will AI replace all of our daily writing?

• ChatGPT is not entirely accurate: It is not entirely accurate, something even OpenAI has admitted. It is also evident that some of the essays written by ChatGPT lack the depth that a real human expert might showcase when writing on the same subject.
• ChatGPT lacks depth like human mind: It doesn’t quite have the nuance that a human would often be able to provide. For example, when asked ChatGPT how one should cope with a cancer diagnosis. The responses were kind but generic. The type of responses you would find in any general self-help guide.
• It lacks same experiences as humans: AI has a long way to go. After all, it doesn’t have the same experiences as a human.
• ChatGPT doent excel in code: ChatGPT is writing basic code. As several reports have shown, ChatGPT doesn’t quite excel at this yet. But a future where basic code is written using AI doesn’t seem so incredible right now.

Limitations of ChatGPT

• ChatGPT is still prone to Misinformation: Despite of abilities of the bot there are some limitations. ChatGPT is still prone to misinformation and biases, which is something that plagued previous versions of GPT as well. The model can give incorrect answers to, say, algebraic problems.
• ChatGPT can write incorrect answers: OpenAI understands some flaws and has noted them down on its announcement blog that “ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers.

Conclusion

• OpenAI’s ChatGPT turned that simple experience into something entirely different. ChatGPT is a path-breaking example of an AI chatbot and what the technology could achieve when applied at scale. Limitations aside, ChatGPT still makes for a fun little bot to interact with. However, there are some challenges that needs to be addressed before it becomes a unavoidable part of human life.

Manis question

Q. What is ChatGPT? Discuss why it is seen as pathbreaking example of an AI chatbot and the limitations?

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Context

• Elon Musk’s medical company, Neuralink, has been accused of causing needless suffering and death to around 1,500 animals in just short few years. Sources indicate that animal testing is proceeding too swiftly, which results in unnecessary suffering and death for the animals.

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What Is Neuralink?

• A device to be inserted in brain: Neuralink is a gadget that will be surgically inserted into the brain using robotics. In this procedure, a chipset called the link is implanted in the skull.
• Insulated wires connected to electrodes: It has a number of insulated wires connected from the electrodes that are used in the process.
• Can be operated by smartphones: This device can then be used to operate smartphones and computers without having to touch it.

The science behind the human brain

• Neurons of the Brain: The brain consists of neurons that transmit signals to cells in the body including muscle, nerve, gland and other neuron cells.
• Functions of each part of the brain: Every neuron is made up of three parts called the dendrite, the soma (cell body) and the axon. Each of this part has its own function. The dendrite receives the signals. The soma processes these signals. The axon then transmits the signals to the other cells.
• Neurotansmitters: The neurons are connected to one another by the synapses which release neurotransmitters. These chemical substances are then sent to another neuron cell’s dendrite causing the flow of current across the neurons.

How Does Neuralink Work?

• Electrodes can read electric signals: The electrodes that are part of the Neuralink will read electrical signals that are produced by several neurons in the brain. The signals are then outputted in form of an action or movement.
• Implanted directly in the brain: According to the company’s website, the device is implanted directly in the brain because placing it outside the head will not detect the signals produced by the brain accurately

What Does Neuralink Do?

• To operate encephalopathy: Neuralink can be used to operate encephalopathy.
• People with paralysis can be operated: It can also be used as a connection between the human brain and technology. This means that people with paralysis can easily operate their phones and computer directly with their brain.
• It will help people to communicate: Its main purpose is to help people to communicate through text or voice messages.
• Wide applications: Neuralink can also be utilised to draw pictures, take photographs and do other activities.appliactions

Conclusion

• Though the Neuralink innovation pushing the boundaries of neural engineering, cruelty over the animals cannot be ignored.

Mains question

Q. What is Neuralink? What is the science behind the human brain and what the neuralink will do?

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