Generative Artificial Intelligence (AI)

(Significance of technology for India, AI, indigenisation of technology and development of new technology)

Generative AI:

-It is a cutting-edge technological advancement that utilizes machine learning and artificial intelligence to create new forms of media, such as text, audio, video, and animation.

-With the advent of advanced machine learning capabilities: It is possible to generate new and creative short and long-form content, synthetic media, and even deep fakes with simple text, also known as prompts.

-Generative AI works by training a model on a large dataset and then using that model to generate new, previously unseen content that is similar to the training data.

-This can be done through techniques such as:

-Neural machine translation,

-Image generation, and

-Music generation.

•Revenue generation: Generative AI can craft sales, marketing, and brand messaging.

•Blogging and reach: Agencies can generate personalised social media posts, blogs, and marketing text and video copies by providing a text prompt to a Generative AI service, like ChatGPT.

•Logo and imagery: DALL.E, a generative image generation service, can also generate original imagery to align with the branding.

•Coding: It can suggest entire functions, snippets, and even fully functioning modules and generate code in real-time right in your editor.

•Synthetic Data:  Generative AI can also be used for generating synthetic data for data augmentation and creating additional training data to train and test AI models to experiment at scale.

•Medical history and related important data:  It can also help health professionals with their medical diagnosis. AI can generate potential and alternative treatments personalised to patients’ symptoms and medical history. For instance, DeepMind AlphaFold can predict the shape of protein.

•Simplifying complex queries: ChatGPT can also assist in providing answers to complex queries and augment search algorithms to generate responses to complex search queries.

•Testing: It can help speed up the iterative development and testing of novel designs.

•Interior 3D Plans: Architecture, machine design, and even house floor plans are all be made by Generative Image and video technology.

Benefits:

• Increased Efficiency: Generative Artificial Intelligence can be used to automate tasks that would otherwise require manual labor. This can help businesses save time and money, as well as increase efficiency e.g., it can be used to generate images and videos quickly and accurately, which can be used in marketing campaigns or other projects.
• Improved Quality:  It can be used to create high-quality images and videos that are more visually appealingthan those created manually and generate text that is more accurate and relevant.
• Faster Results: It can create images and videos in a fraction of the time it would take a human to do the same task
• Cost Savings: By automating tasks, businesses can reduce their labor costs and save money.
• Improved Decision Making: e.g., it can be used to generate data that can be used to make decisions about marketing campaigns or product development. Applications in the medical field can help in better diagnosis.
• Increased Creativity: Businesses can generate new ideas and concepts that can be used to create new products or services.
• Improved Customer Experience: Businesses can generate content that is more accurate and relevantto their customers. This can help businesses create a better customer experience and increase customer satisfaction.

• Concerns around AI use
• Ethical:  It raises ethical concerns about the potential for biased or inaccurate content to be generated and disseminated.
• Responsible Development:  If not designed and developed responsibly with appropriate safeguards, Generative AI can create harm and adversely impact society through misuse, perpetuating biases, exclusion, and discrimination.
• Perpetuates biases: Generative AI systems can perpetuate and amplify existing biases and exclusion If the models are trained on biased, non-inclusive data.
• Fake news & hate words or speeches: Generative AI systems can create content for malicious purposes, such as deepfakes, disinformation, and propaganda.
• Access to privacy: These systems can potentially access sensitive information, raising concerns about data privacy and security.
• Incorrect data and diagnosis: It may also produce low-quality and less accurate information, specifically in the context of complex engineering and medical diagnosis.
• Accountability can not be fixed: It can be challenging to determine who is responsible for the content generated by a generative AI system — the acquisition and consent model around the training data and intellectual property issues make it difficult to hold anyone accountable for any harm resulting from its use.

Way forward:

• First, to address bias and fairness, researchers can use techniques such as de-biasing and fair representation learning, which can help to remove biases present in the training data.
• Second, Researchers can also use techniques such as counterfactual data generation, which can help to generate more diverse and representative training
• Third, there is need to add rigour and responsibility to developing AI technology, develop and enforce ethical guidelines, conduct regular audits for fairness, identify and address biases, and protect privacy and security.
• Fourth, There is need to add adequate policy, regulation, awareness, and education guardrails to develop and use Generative AI services ethically and responsibly. China has proposed a policy for the same. EG: the regulation mandates people using the technology to edit someone’s image or voice, to notify and take the consent of the person in question.
• Fifth, Intellectual property law must find a way to protect artists from copies that erode the value of their original work, but at the same time encourage them to continue to be inspired by others