The potential of generative AI: creating media with simple text prompts

Source: The post is based on the article “The potential of generative AI: creating media with simple text prompts” published in The Hindu on 9th January 2023

What is the News?

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

What is Generative AI?

Generative AI is a type of artificial intelligence that involves creating new, original content or data using machine learning algorithms. It can be used to generate text, images, music, or other types of media. 

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. 

What are the different ways Generative AI can be used?

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.

Reduce the burden of human research: It can help 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. 

Help in designing: It can also help create and simulate complex engineering, design, and architecture. It can help speed up the iterative development and testing of novel designs. 

Personalized Health treatments: It can also help health professionals with their medical diagnosis. AI can generate potential and alternative treatments personalized to patients’ symptoms and medical history. For instance, DeepMind AlphaFold can predict the shape of the protein.

What are the concerns related to Generative AI?

Deepfakes: Generative AI, particularly machine learning approaches such as deepfakes, can be used to generate synthetic media, such as images, videos, and audio. Such AI-generated content can be difficult or impossible to distinguish from real media, posing serious ethical implications. Such media may spread misinformation, manipulate public opinion, or even harass or defame individuals.

Inaccuracy problem: Generative AI uses machine learning to infer information, which brings the potential inaccuracy problem to acknowledge. Also, pre-trained large language models like ChatGPT are not dynamic in terms of keeping up with new information. 

Increase in Biases: Large language models enable human-like speech and text. However, recent evidence suggests that larger and more sophisticated systems are often more likely to absorb underlying social biases from their training data. These AI biases can include sexist, racist, or ableist approaches within online communities.

Misuse: Nefarious actors may use AI-generated media to manipulate people and influence public opinion. These systems can potentially access sensitive information, raising concerns about data privacy and security. It may also produce low-quality and less accurate information specifically in the context of complex engineering and medical diagnosis. 

Risk of Unemployment: Although it is too early to make certain judgements, there is a risk that generative AI could contribute to unemployment in certain situations. This could happen if generative AI automates tasks or processes previously performed by humans, leading to the displacement of human workers.

 

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