After the introduction of ChatGPT, the focus of numerous governments, corporations, and businesses has shifted towards Artificial Intelligence, particularly in the realm of generative AI. The mainstream recognition of generative AI technology began to gain traction in November 2022 with the launch of ChatGPT by OpenAI. As per various reports, the market for generative AI is likely to double every two years in the coming decade.
What is Generative AI? Where does Generative AI fit in the AI discipline?
Generative AI- Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery and audio. The term ‘Generative’ refers to the ability of the models to create new data based on certain input parameters. For ex- A generative model is used to generate facial images by providing a set of parameters such as the eyes, hair, or skin colour etc.
Relation between AI, Machine Learning, Deep Learning & Generative AI
| Artificial Intelligence (AI) | AI is a discipline which focuses on formulating theories and methodologies for constructing machines that emulate human thought processes and behaviours. |
| Machine Learning (ML) | Machine learning is a subfield of Artificial Intelligence. ML involves the development of programs that train models using accessible data from sources such as webpages, articles, books, etc. These trained models are then used to make useful predictions for new and never-seen before data. The most common ML method to train the models is the supervised learning method. |
| Deep Learning | Deep learning is a subset of Machine Learning. Deep learning is a type of machine learning that uses artificial neural networks. These multilayered and interconnected neurons (inspired by the human brain), are used to process complex data and make predictions. |
| Generative AI | Generative AI is a subset of deep learning. It uses artificial neural networks to process data using supervised learning methods. This large-scale supervised learning technology is termed the Large Language Model (LLM). |
What are the advantages of Generative AI?
1. Writing and advertising- Generative AI is being used as a brainstorming companion by the writers. For ex- Drafting press releases, language translation, creating new advertisements based on existing ones.
2. Reading- Apart from writing, this technology is used as a reading tool. For ex- Auto Reading customer mails and segregating them based on complaints.
3. Chatting- Generative AI is also used for many special-purpose chatbot tasks. For ex- Government chatbots to help citizens get access to the right information on various schemes and policies.
4. Security Services- This AI technology can create front-on photos from photos taken at different angles and vice versa. This can be used in face identification systems to secure the airports, international border check-points etc.
5. Enhanced capability of Search Engine Services- Generative Artificial Intelligence has the capability to take search engine services to the next level. For ex- Text to Image translation to provide search results.
6. Improving Healthcare System- This technology has the potential to revolutionise the healthcare sector by improving the accuracy of diagnosis. For ex- Conversion of X-ray or any CT scan images to real images can improve the accuracy of diagnosis.
What are the Challenges with the Technology?
1. Increased Biases- Generative Artificial Intelligence systems can perpetuate and amplify existing biases. These systems can generate biased outputs like offensive language, demeaning imagery, and prejudicial content, if they are trained on biased, non-inclusive data. For ex- US rights group observation about an AI-based generative imagery programme showing images of only white men for the prompt ‘CEO’.
2. Threat of Job Losses- There are fears of job losses as this technology can prove to be more cost-efficient and productive to firms as compared to human capital. For ex- Customer service jobs are under threat from the AI chatboxes (Zomato’s Zia).
3. Use for Malicious Purposes- Generative AI systems can be used to create content for malicious purposes, such as deepfakes, disinformation, and propaganda. Nefarious actors may use AI-generated media to manipulate people and influence public opinion, like use for Post Truth Doctrine.
4. Concern over Data Privacy- There are emerging concerns in regard to data privacy in using generative AI technology. For ex- Use of AI in healthcare involves collecting private information about individuals, which raises concerns about data privacy.
5. Issues Related to Copyright and plagiarised contents- Generative AI technology has been associated with copyright violations and production of plagiarised content. For ex- Getty Images has sued Stable Diffusion (Generative AI Company), accusing them of copyright violations.
6. Limitations in Creativity- Generative AI systems lack creativity, originality and human ingenuity as they use past data as a template for future work.
7. Environmental Concerns- AI systems require a lot of computing power, which have grave implications for the environment. For ex- According to analysts, training a transformer model just once with 213 million parameters can emit carbon emissions equivalent to 125 flights between New York and Beijing.
What should be the way Forward?
1. De-biasing while training the AI- We must ensure fairness of the information which is being fed into the system, to ensure that AI doesn’t perpetuate or amplify social biases, like gender and racial biases.
2. Transparency of information- Users should have transparent information about the limitation and risks of AI.
3. Privacy protection- The user data and confidentiality must be protected to ensure user privacy. For ex- Strict implementation of data protection laws.
4. Ethical use of AI- We must ensure that AI is used only for beneficial purposes. The push must be made towards universal adoption of the Bletchley Declaration by all the countries.
Ai has the potential to give society intelligent guidance on how to approach some of the biggest problems, like climate change and pandemics. In the coming times, AI will contribute to longer, healthier, and more fulfilling lives worldwide if used responsibly.
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