Editorial of the Day: The Potential of Generative AI- Creating Media With Simple Text Prompts (The Hindu)

In News: Top technology companies, like Microsoft, Google, Facebook, and others, have commercial AI labs researching and publishing academic papers to accelerate AI innovations.

• Generative AI is a cutting-edge technological advancement that utilises 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.

• However, it also raises ethical concerns about the potential for biased or inaccurate content to be generated and disseminated. It is important for developers and users of generative AI to consider the potential impacts and ensure that the technology is used ethically and responsibly.

Applications of Generative AI

• Generative AI can craft sales, marketing and brand messaging: Agencies can generate personalized social media posts, blogs and marketing text and video copies by providing a text prompt to a Generative AI service like ChatGPT.
• Efficient communication: The service can quickly iterate different text by simply tweaking the prompt to effectively communicate with the audience.
• Logo and imagery: DALL.E, a generative image generation service, can also generate original imagery to align with the branding. Many startups are exploring services like DALL.E2, Bing Image Create, Stable Diffusion, and MidJourney to create their brand logo and to align the same with Generative AI text messaging.
• Better copywriters: Instoried is using Generative AI for marketers to become better copywriters.
• Generate code in real-time: GitHub, Copilot6 and ChatGPT1 can generate code and help with developer productivity. It can suggest entire functions, snippets, and even fully functioning modules and generate code in real-time right in your editor. ChatGPT can also help you write code to build a technology service or integration quickly.
• 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.
• Reduce the countless hours of human research: Generative AI can sift through numerous legal research materials and produce a pertinent, specific, and actionable summary. As a result, it can reduce the countless hours of human research and enable them to focus on more complex and exciting problems.

• Accelerate the discovery of new research: Generative AI can accelerate the discovery of new research, drafting and synthesising documents and reports. Wranga is using AI to generate media reviews to help parents to monitor and steer their children’s content consumption habits.
• Simplifying complex queries: ChatGPT can also assist in providing answers to complex queries and augment search algorithms to generate responses to complex search queries.
• Complex design creation: It can help create and simulate complex engineering, design, and architecture.
• Speed up the iterative development: 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.
• 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.

Concerns Around AI use

• Impact on Society: Generative AI can create harm and adversely impact society through misuse, perpetuating biases, exclusion, and discrimination.
• Ethical concerns: It raises ethical concerns about the potential for biased or inaccurate content to be generated and disseminated.
• Perpetuates and amplifies existing biases: If the models are trained on biased, non-inclusive data, they will generate biased outputs, such as offensive or discriminatory language, demeaning and degrading imagery, and prejudicial content.
• Create content for malicious purposes: Generative AI systems can create content for malicious purposes, such as deepfakes, disinformation, and propaganda. It can also generate offensive or inappropriate content. Nefarious actors may use AI-generated media to manipulate people and influence public opinion.
• 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: 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

• Big tech has taken corrective actions to mitigate bias issues and develop AI responsibly in the last few years.
• It is essential to carefully consider the potential harms, threats, and concerns of Generative AI systems and ensure that they are used responsibly and ethically.
• Therefore, we must add an adequate policy, regulation, awareness, and education guardrails to develop and use Generative AI services ethically and responsibly.

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