Generative Artificial Intelligence has traversed a captivating journey of advancement since its inception. Over time, with significant strides in machine learning and deep learning, it has emerged as a remarkable, often astonishing, discipline aiming to generate ideas, replicate human capability, and bridge the chasm between human understanding and computer intelligence.
Where we’re at today, GenAI stands as a transformative force, reshaping industries, enhancing possibilities, and ensuring innovation never stops. It’s become an avant-garde, relentlessly pushing the boundaries of efficiency and productivity.
It started out by dominating the realm of gaming and entertainment, delivering user experiences that are interactive, engaging, and best described as unforgettable. However, it’s now helping domains of healthcare and medicine, manufacturing, and design, IT services transcend the confines of traditional methods and adopt newer, better ways of working; a transformative powerhouse, indeed.
The realm of Generative AI holds an undeniable allure, brimming with opportunities and untapped potential.
India isn’t taking a backseat when it comes to exploring this space. The government, academia, and industry stakeholders are recognizing the plenty of use cases GenAI promises to unlock and are actively engaged in exploring the frontiers. The country stands poised to embrace and contribute to its growth, leveraging its talent, entrepreneurial spirit, and supportive policies to shape the future and mark a presence on the global stage.
However, it’s fair to point out that while many are excited about how artificial intelligence can shape the future, there is a lot of hesitation and skepticism. Will AI replace me? Will AI dominate? Is AI safe and ethical? How can the benefits be realized throughout society?
These burning questions are endless, and organizational players need to dig deep and answer them for the benefit of everyone. Regular communication, collaboration, idea sharing, and progress mapping is the only way forward.
Global Talent Exchange recently organized a virtual roundtable discussion as part of our Technology Game Changers Series on “Generative AI: The Next Wave Of Disruptive Innovation”.
The riveting dialogue was moderated by Madhav Bissa (Program Director at Nasscom AI). He brings to the table an exceptional skill set, with his expertise lying in the areas of Strategy and Business Analytics. Apart from his corporate achievements, Madhav is also an accomplished academic, serving as a visiting faculty at various institutions. Currently, he works to connect ecosystem players like governments, industry, academia, and startups to create a socio-economic impact through Data and AI.
The panel consisted of 9 distinguished industry leaders who brought their passion, energy, and expertise to the discussion, actively engaging in thought-provoking discourse and sharing invaluable perspectives.
Our founder, Avinash Bichali, set the tone of the discussion by talking about the unprecedented response that ChatGPT received; just 5 days for 1 million users! In the past, it took Apple more than 2 months, Facebook more than 10 months, and likewise Netflix, etc. to accomplish the same goal.
Madhav went on to pose the first question to the visionaries.
What are some key milestones in the evolution of intelligent machines? Which tech advancements have been most significant in enabling the current capabilities of AI?
A panelist sought out answering this by carefully outlining the 3 stages through which Generative AI has evolved over the years. The first stage was ‘Symbolic AI” which was agent-based, had hard-core rules, and knowledge was encoded into it by humans. It helped enhance productivity and unlock a stream of thought that made people think about what else might be possible. We later went on to a stage of ‘Connectionist AI’. We, as a community of researchers and technologists, learned how the brain and neural systems worked. It was less computational and more focused on embedding human thinking into a computer. The data available was less. Lastly, what we are currently privy to, is ‘Modern AI’. It has evolved through several practices and techniques of algorithms. Data infrastructure is available, as are data processing capabilities. Relationships are being captured and these unique relationships are being put together to formulate a human-like algorithm/tool/product.
Several Artificial intelligence paradigms have occurred- evolutionary, swarm intelligence, and even looking toward nature for certain answers. We’ve taken massive strides, not steps, forward and now could eventually reach a stage where AI could replicate human emotions as well.
How do the current capabilities of intelligent machines compare to those of humans? In which key areas do AI systems still lag behind human intelligence? What is the current status of adoption across businesses and industries?
Most people now, with what the media is feeding them, believe that AI is coming after their jobs. There is a lot of fear that it will inevitably replace humans across functions and will even become more intelligent than them. However, the truth is that without humans in the loop, you can never get 100% out of a technology. Human expertise must always complement tech, especially when it is as complex as this. For example, in data, accuracy is a challenge. We cannot let automation take over completely; it might segment and organize the data, but a person is required to come in and verify it.
According to one panelist, AI would impact different industries differently. Organizations need to leverage the strength of AI and human intelligence together to increase efficiency and productivity. When it comes to being creative, there is no right or wrong answer; there are multiple ways of correctness, all of which might be perceived and appreciated well by different audiences. Thus, AI has the potential to impact and revolutionize the entertainment and creativity industries the most- be it film, music, video, etc. It can be used to generate hyper-realistic videos and images; in fact, it is already being used in many companies around the world.
The experts in their respective fields will most certainly not be replaced, however, there’s no denying that AI will challenge the existing paradigm.
The conversation was then shifted on to actual use cases.
What are some of the most promising and exciting applications of generative AI?
GenAI can also be called creative Ai as it continues to give us new ideas, and solutions. The possibilities and use cases are endless.
One thought leader listed out the top 3 use cases that they’re most excited about, with the first being data augmentation. An example was cited about the problems and obstacles of car damage image model creation; when done manually, there are several errors and things to keep in mind and is extremely labor intensive. However, AI can get the task done perfectly in minutes. The next was pair programming. The panelist pointed out that coders and programmers must get comfortable with using Copilot. AI can comment on code, perfect and optimize it, and even create tests on it. It enhances human intelligence. The last one was the increasing business adoption of technology- AI can translate between languages and between user personas. People can render business-specific contexts and make the end result more “readable” for users.
Just a few months ago, creativity was considered to be a domain exclusive to humans. However, AI was able to observe and create. Now, the human role will change from being the creator to being an editor. The number of jobs is not likely to reduce, however, the type of jobs will change. The IT industry will be disrupted massively. The knowledge quotient of planet Earth will multiply exponentially as now, it is language independent. Everyone can benefit from information and knowledge from any corner of the world.
From the Indian perspective, the country is extremely vast and diverse. The disparity in terms of language usage, financial health, and more, is huge. Thus, generative AI can help the same piece of information be understood in multiple ways. Content personalization, according to individual needs and requirements, is a massive use case for India. It can help people in improving how they write and communicate with each other.
One panelist with expertise in the healthcare domain was asked about the health and medicine-specific use cases of Generative AI.
There are several possible use cases already and even more will evolve once the technology becomes more mainstream and better accepted. AI can be used for medical imaging to create synthetic images. It can be used to reduce the administrative burden as documentation and manually recording patient data takes up a lot of time at present for both the front-desk staff as well as healthcare providers; automation can take over this. Predictive maintenance is another interesting use case for Generative AI. From a manufacturing standpoint, it can be expensive and time-consuming to continuously have to repair and maintain medical devices when they fail. AI can help predict when the device is like to collapse, helping to schedule repairs well in time. AI-driven bots can be used for surgical operations. There is also the use case of personalized medication and precision medicine; people can receive crafted and personalized treatment plans and help doctors suggest the best mode of treatment. Above all, AI has the potential to provide medical expertise 24/7 throughout every corner of society. However, there are a lot of privacy and ethical concerns that are posing a challenge right now. If we can balance them and arrive at practical solutions, the future is great.
The panelists were then guided by Madhav on to the most burning question: What are the most pressing ethical and privacy concerns associated with the use of Generative AI? How can AI be used in a safe, sustainable, and transparent manner, preventing potential misuse? What safeguards must be put in place?
Regulation is essential for AI to be made more responsible. There are several trademark issues, plagiarism concerns, image manipulation/deep fakes, data privacy concerns, copyright infringement, and much more.
The data has been thrown open to the public for use, but no one is regulating its use. There is no regulator to differentiate between what is right or wrong for responsible products to be created, which is why we’re witnessing new roles like Chief Ethics Officer come about.
There are several biases that society has been holding on to for the longest time, which is reflected in the way AI answers prompts. We can see this in a positive way; GenAI can actually help us unfold these age-old biases so that we can move on to overcome them.
One panelist pointed out that instead of talking about the use of Generative AI, we need to address how these tools are being created in the first place.
Yet another panelist pointed out how misinformation along with data security was the biggest challenge. Technology evolves over time- always, at first, it is kept within the domain of a limited few people, whereas soon enough, several get their hands on it; like the computer, mobile phone, etc.
The panelist feels that GenAI is going through a hype cycle at present. Soon this hype will die down, and that’s when it will flourish. It will enter the mainstream and real-life broad applications will be discovered. The technology is not very mature right now, and a lot is left to be desired before its thrown open to the public. Thus, it is being misused.
About how to overcome these problems, the thought leaders pitched in with their personal experiences and insights.
One panelist felt that cognitive skills must be taught at the base level- people must be taught how to handle and use technology that is as powerful as this. Tech is the means to an end, not the end.
More transparency is required and it is both a collective and individual responsibility. We owe it to future generations to leave something behind that is not dangerous but that helps them in the large scheme of things.
From a startup perspective, one speaker discussed how they manage to ensure privacy and ethics never pose a challenge. They ensure their service/tool is used to enhance content and save people’s time. Deception is never the way to go. It’s best to inform people of the use of AI and ensure transparency. This is the only way to actively build trust with the end user.
An important sub-question: How do we truly reinforce and practice “tech for good”?
Once again, transparency is the way to go.
Clients/patients/users should be made aware of how their data is being utilized and how decisions are being made by AI algorithms. The masses need to be educated; at present, large organizations are only training people within on how to use AI, but we also have an obligation toward society.
There also needs to be accountability for decision-making.
The conversation changed course and was moved on to another, just as important, topic.
Why is collaboration between the government, industry, and academia important? In what way can these individual verticals leverage their respective strengths to develop AI further?
The govt., industry, and academia are currently functioning in silos. There is a distributed thinking mindset. To come out of this, we need a planned thinking mindset. We need to figure out how ready we are, how literate we are, how further along are we with regard to tech adoption, and whether or not we’ve taken the necessary steps to ensure security. This isn’t the responsibility of just one vertical; all must collaborate to do this.
There needs to be more spending on research, training, and development.
Dynamic curriculums must be introduced in Universities that are flexible to change and can teach the latest trends in the industry and market. Concepts are not enough; students must be given the opportunity to experience the applications too. Scenario planning is another aspect essential for the end goal of digital transformation.
If we continue progressing at this rate, India will soon be at the forefront of AI innovation.
The most burning question of all, something everybody is keen to know.
Are humans and AI in competition with each other? If not, how can we work to change this perception?
Technology is only automating certain tasks. It cannot replace humans but is merely an enabler. It will take time for people to come to terms with this new reality and actively adopt and integrate it into their lives. We are not competing with AI. It can help us get rid of the most laborious tasks in our jobs, freeing us to work faster and better and focus on the most complex responsibilities. AI is not replacing you. Ensure you’re constantly ahead of the game by staying aware of the latest developments in your field and focus on upskilling.
How can AI be made inclusive and accessible to all?
As mentioned before, AI can help unfold biases. It can help create solutions through healthy debate and alternative perspectives. It can help individuals being held back by mental health challenges integrate into society better and contribute to the best of their abilities. AI can help you optimize your life and make you a better individual.
Regarding inclusivity, several marginalized and minority groups can benefit from government schemes now. Pilferage was first 85% but now after the JAM Yojana (short for Jan Dhan-Aadhaar-Mobile), it’s reduced to almost nill because of the digital transformation that took place. The government has also set up rural kiosks to understand what the people need.
Last, but not least.
What are the reasons for the massive skill shortage in AI in India? Which areas of expertise are particularly lacking?
According to some panelists, universities in India are not equipped with the right type of courses/curriculums- a change is required there. Industries here are not risk-takers and do not want to delve into a realm that isn’t properly explored yet. We must evolve from a service provider mindset to a product development one. There needs to be an emphasis on creativity and competency, and we need people who are critical thinkers and storytellers, those people that can sell ideas to stakeholders and are change-ready and flexible. We need more mathematicians with strong computational skills here. India has an excessive quantity of talent, but unfortunately, we lack in quality of skill and knowledge. Organizations here are investing a lot of money to attract and retain the best talent and taking steps like information-sharing sessions, upskilling initiatives, and providing a robust career path to all employees. There is also a need to turn our attention toward providing jobs in Tier II and Tier III cities to people who might not have received an education from the best universities but still are talented and capable.
We also need to enhance our talent pool by attracting talent from across borders. One panelist, who is a successful startup founder, narrated his personal experience of how NRI techies over the world are now choosing to come back to India and work in some of the organizations that are doing some transformative work; this is both because of the booming ecosystem in India as well as the disruption in the West.
The discussion served as an eye-opener for all present, and everyone walked away enriched with new insights and ideas.
This closed-door conference was the 11th in our Technology Game Changers Series and we are gearing up for the next. Stay tuned!
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