Home Hot TopicsArtificial Intelligence The Next Big Thing in AI And ML – Trends That Will Drive Innovation In 2022 and Beyond

The Next Big Thing in AI And ML – Trends That Will Drive Innovation In 2022 and Beyond



In an interview with CIO AXIS, Sukanya Mandal, IEEE Senior Member, discusses the trends that will take the center stage in AI/ML in 2022.

1. How will Artificial Intelligence impact the future of work and workspace?

Artificial intelligence has accelerated digitization and brought in many new technological possibilities that are making huge strides on the socio-economic front and impacting industries across the verticals. The future of living and working, thanks to AI, will be more advanced and efficient, supplemented by automation and machine learning. A recent paper published by the MIT Task Force on the Future of Work shows that AI continues to drive large-scale innovation, fueling many existing industries, creating more jobs and has the potential to create new growth for sectors. It will make it easier for organizations to spot problems and address them more effectively.

AI and ML will also pave the way for hyper-automation for industry 4.0 and beyond, thereby boosting the importance of “human skills” such as problem-solving, quantitative skills, and creativity, which will further create specializations in job roles. The most significant benefit of this will be allowing humans to focus on complex and rewarding projects while AI deals with tedious and repetitive tasks. Additionally, AI can make data-driven decisions that eradicate the tendency of humans to be influenced by their feelings and underlying biases while making important decisions.

AI will also positively impact diversity at workplaces. The application of AI in various areas in the workplace will result in a lot of job shifts. For instance, with automation and intelligence, dealing with heavy machinery was typically a male-dominated labor force. It no longer has to be restricted to just males anymore as females could be trained to operate such machinery, thus democratizing the workforce. The future workplace will consist of people and machines working together to improve the way we work.

2. How will AI contribute to the Industrial Revolution 5.0?

The fifth Industrial Revolution will be an enhancement on Industry 4.0 and will be focused on creating personalized services for a sustainable, people-centric, resilient and competitive. Artificial intelligence and cognitive-based services will play a huge role in facilitating the interaction and cooperation between man and machines. New age artificial intelligence technologies like blockchain, the internet of things, AR/VR, machine learning, deep learning, and the most recent – metaverse – will contribute to enhancing manufacturing – combing people, processes, and machines. This technical enhancement will have an overall effect on the economical production and the application of artificial intelligence will facilitate rather than eliminate employment. The collaborative dimension is the foundation of the next revolution, which is both imminent and unavoidable.

Hence, we will witness a demand to further explore the use of artificial intelligence and its applications to improve the quality of manufacturing, supply chain management, and smart cities in Industry 5.0.

3. Which industries/areas are going/most likely to witness the AI/ML driven mechanism?

Healthcare: Artificial intelligence has the potential to revolutionize the healthcare industry with innovative solutions like telemedicine, remote patient monitoring, smart wearables, nanorobotics. The future of AI in healthcare is a step toward democratizing healthcare for the benefit of both patients and healthcare professionals while also making it less expensive and more accurate through AI-powered predictive care.

Banking and Insurance: From early fraud detection to assisting banks in implementing risk mitigation practices, AI will enable the banking and finance industries in making huge strides. Furthermore, AI will also allow organizations to monitor payment networks in real-time, analyze data, and assess transaction risks. Banks can also harness the power of this intelligent technology to detect money laundering and monitor cyber threats. In the insurance industry, AI technologies are already being used to detect fraud and verify insurance claims.

Transportation: Transportation is another industry that is being revolutionized by AI. We’re already seeing the emergence of self-driving cars.AI is also being utilized to optimize vehicle health especially in connected cars and electronic vehicles.

Marketing: With AI-powered tools and algorithms, marketers will be able to interpret and analyze the dynamics of various metrics like consumer behavior, ad placements, and improved content creation. With personalization increasingly becoming the focus of the industry, it is likely that the market will rely more and more heavily on artificial intelligence technologies to enhance consumer experiences. AI and machine learning will be used in the next generation of marketing tools to make communications more relevant than ever before.

4. What are the common misconceptions about AI and the fear associated with AI driven tools? How can it be resolved?

The most common myth concerning Artificial Intelligence is that it will replace humans in the workplace. However, AI-based systems are designed to interact with humans in shared workplaces whose application is aimed at facilitating jobs rather than eliminating human intervention or employment. According to most scientific estimates, AI-driven automation is expected to create fundamental shifts in roles and create more jobs than it will displace. Moreover, AI in the workplace has the potential to improve how people and businesses do their jobs. This revolution is aimed at supporting humans. The goal is to find a perfect balance where machine-human interaction can provide the most benefits.

Secondly, it is also widely believed that AI algorithms are completely objective and neutral processes. The reality is that AI is only as good as the people or companies who built it. AI is based and built on the data that is collected by humans and is further trained with machine learning (ML) algorithms that are created by humans. Hence it cannot be certainly said that AI is unbiased or neutral.

Lastly, another common misconception is that the sole use case for AI is automation. AI can be used for two main purposes: automation and expansion.

5. What are some of the trends in AI/ML that you think will take the center stage in 2022 and beyond?

Tiny ML: While large-scale machine learning applications are available, their usability is limited. We can achieve lower latency, lower power consumption, lower required bandwidth, and ensure user privacy by running smaller-scale ML programs on IoT edge devices. Because the entire set of raw data is not sent to a data center (only the processed information is sent to the cloud), latency, bandwidth, and power consumption are greatly reduced. And because the computations are done entirely locally, privacy is also preserved. This emerging innovation has numerous applications in fields such as predictive maintenance for industrial facilities, healthcare industries, agriculture, and others.

Auto ML: Auto ML aims to make it easier for developers to create machine learning applications. Off-the-shelf solutions have been in high demand as machine learning has become increasingly useful in a variety of industries. Auto-ML aims to bridge the gap by providing a simple and approachable solution that does not require ML experts.

Deepfakes, generative AI, and synthetic data: Generative AI refers to artificial intelligence algorithms that can generate new plausible content from existing content such as text, audio files, or images. In other words, it enables computers to abstract the underlying pattern associated with the input and then use it to generate similar content. It is thought to have enormous potential for creating synthetic data for the training of other machine learning algorithms. To train facial recognition algorithms, synthetic faces of people who have never existed can be created, avoiding the privacy concerns associated with using real people’s faces.

Low Code or No-Code ML: The low code or no code ML processes do not include time-consuming processes like modeling, algorithm development, collecting data, retraining, debugging, and so on. Hence, it is economical, simple, and easy to deploy and implement these. Additionally, this system of solution development does not require expert Data Science staff.

Augmented Business Process and Systems: 2022 will give a boost to all types of automated systems powered by AI, like Metaverse, Mixed Reality and augmented Data Management and analytics, to achieve operational excellence, cost efficiencies, and resilience. The combination of cloud with robotic process automation (RPA) and IoT, will create a huge impact and make AI-augmented automation a dream come true for businesses.

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