Generative Artificial Intelligence (GAI), though in its initial stages, is gradually making an impact in various fields as technology continues to evolve. Initially employed in automating repetitive processes during digital image and audio correction, GAI has rapidly grown to focus on generating new content like images, text, audio based on rules and patterns learned from data.
One can attribute the growth of GAI to the advent of advanced generative models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These models are trained on extensive data and have the capacity to generate new outputs akin to the training data. For instance, a GAN trained on face images can create new, synthetic yet realistic face images. Machine learning and deep learning, inherently focused on generative processes, can also be counted as types of GAI.
Applications of GAI
From producing unique art pieces that push traditional boundaries to helping musicians explore new sounds, the applications of GAI span multiple sectors. The DeepDream Generator, an open-source platform, uses deep learning algorithms to create surreal, dream-like images. DALL·E2 by OpenAI generates new images based on text descriptions. AI algorithms in AIVA help compose original music in various styles.
In healthcare, GAI improves medical diagnosis and treatment efficiency by generating new medical images and simulations. In manufacturing and robotics, it optimizes processes, thereby improving efficiency and quality. In computer graphics, GAI helps create more engaging experiences with new 3D models, animations, and special effects.
GAI’s Significance for India
With the AI sector’s growth rate estimated at 20-25%, AI employment in India is about 416,000 professionals. By 2035, AI is expected to contribute an additional USD 957 billion to India’s economy.
Concerns Related to GAI
Despite its potential, GAI presents several concerns. Ensuring high-quality and accurate outputs requires advanced generative models that can accurately reproduce patterns learned from data. Biased training data can also lead to biased outputs, resulting in discrimination and amplification of societal biases.
Training GAI models require access to extensive data, including personal and sensitive information. This poses a privacy risk as this data could be used unethically for targeted advertising or political manipulation. There’s also the ethical dilemma over responsibility since GAI models can create new content like fake news without knowing who is responsible.
Another significant concern is job displacement due to automation of various processes by GAI, raising ethical questions about AI’s use and potential impact on workers and society.
Indian Initiatives Related to GAI
The Indian government has published the National Strategy for Artificial Intelligence to foster an ecosystem for AI research and adoption. The National Mission on Interdisciplinary Cyber-Physical Systems established the Technology Innovation Hubs on AI and Machine Learning at IIT Kharagpur to train the next generation of scientists, engineers, technicians, and technocrats in AI. Also developed is the Artificial Intelligence Research, Analytics and Knowledge Assimilation Platform, a Cloud computing platform designed to establish India as a pioneer in AI among emerging economies, transforming sectors like education, health, agriculture, urbanization, and mobility.
Way Forward
To improve GAI models’ accuracy and reliability and address related ethical issues, more research and development are needed. Regulations and standards must be put in place to ensure responsible and ethical use of GAI. Collaborations between stakeholders, including industry, government, academia, and civil society, are crucial for this.
GAI models are only as good as their training data – ensuring ethical and unbiased data collection respects individuals’ privacy and does not reinforce existing biases is essential.
While GAI offers immense potential, careful and ethical application coupled with robust regulations is necessary to truly harness its benefits.
