Is there any industry in the modern world has been left untouched or without the use of artificial intelligence (AI)? Short answer is, no. From autonomous vehicles (self-driving cars), robots in manufacturing, faster disease detection in health care, democratization in education, computer vision warfare to image recognition on your phone, AI is everywhere.
“Lots of industries go through this pattern of winter, winter, and then an eternal spring,” former Google Brain leader and Baidu chief scientist, Andrew Ng, told ZDNet in 2018. “We may be in the eternal spring of AI. The global investments made in AI indicate a promising potential for the world. Of the 9,100 patents received by IBM inventors in 2018, 1,600 (or nearly 18%) were AI-related. In the same year, MIT announced a USD 1 billion plan to create a new college combining AI, machine learning and data science. It was the largest financial investment in artificial intelligence by any US academic institution at the time.
What’s the fuss about?
The global investments made in AI indicate the promising potential for the world. Of the 9,100 patents received by IBM inventors in 2018, 1,600 (or nearly 18%) were AI-related. In the same year, MIT announced a USD 1 billion plan to create a new college combining AI, machine learning and data science. It was the largest financial investment in artificial intelligence by any US academic institution at the time.
In 2019, Microsoft invested USD 1 billion in OpenAI, a research lab established and funded by Elon Musk and Sam Altman. Tech giants, such as Amazon, Apple, Baidu, and Google, are investing billions of dollars in AI for their products and services.
Predictably, the future of jobs in AI looks bright. An AI specialist is the top-rated job on the LinkedIn Emerging Jobs Report for 2020. With an annual growth rate of 74% for this position, every industry is competing for AI talent to devise, manage and optimize strategic plans for their AI system. AI specialists can expect an average annual base salary of USD 127,451.
For a deeper dive into what makes AI almost invincible in the 21st century, we spoke to Brian Subirana, director of the MIT Auto-ID Lab and director of the MIT and Accenture Convergence Initiative for Industry and Technology.
In conversation with Brian Subirana
Emeritus: What makes AI and its potential so powerful for the future?
Brian Subirana (BS): For anything to have an impact, it needs to be adopted by the world. What makes the adoption of artificial intelligence so easy is that the machine-learning algorithms used for AI technologies can learn almost anything; they can often also outperform humans. So, organizations are using them for automation or to augment employee productivity among other things. This lowers costs and makes AI integration a great business model. Another thing that makes AI so big is that it has the “hype factor.” Everyone is talking about it, and so everyone is looking into it. That’s because AI has become appealing in the media as something that might replace human intelligence.
Emeritus: For those who want to learn the design principles and applications of AI, what are some prerequisite skill sets required?
BS: Developing AI projects is not so much about a specific technology skill set but more about choosing which parts of its technology are relevant for your field and how you want to stay up-to-date with that knowledge. For those that want to get into AI technologies such as deep learning I’d say knowledge of calculus, linear algebra, statistics, and probability is beneficial. Basic Python experience and some basic programming skills can also be helpful but are by no means necessary.
Emeritus: How challenging is the successful creation of AI products and services?
BS: The biggest challenge is successfully implementing all four principles of AI product design together. These include:
- The intelligence in the human brain that you want to convert to artificial intelligence
- How the AI technology will become operational in a business process and how it fits strategy
- Your IP approach, i.e. how you collect, analyze and manage your data
- The software development of your AI product
But these challenges are also exciting. When these four stages work together, that’s when the real magic happens.
Emeritus: Once skilled in AI, what is the range of professional paths available?
BS: There are two main ways individuals can use the knowledge of AI. One is having a better understanding of how AI is working or can work in your company to accelerate growth. The second is to lead the design of AI for solutions in your organization. I’d also add that AI in the healthcare industry isn’t being used to its full potential. So, there is a lot of scope for professionals to drive change there.
Who is this course for?
According to a recent report by PWC, 49% of global CEOs state that digital transformation technologies, including AI, will be their top area for long-term investments.
Still, wondering whether you should learn about designing AI products? Our MIT xPro Designing and Building AI Products and Services identified specific job profiles that will benefit from the program:
- Anyone involved in an AI project, especially those who interface with the design and implementation
- Technical product managers in charge of machine learning and AI-based products in their organizations
- Technology professionals who design and develop technology solutions aligned to their organization’s needs
- Technology consultants who focus on the analysis, design, and development of technology solutions for clients
- Founders of AI start-ups who build AI-driven applications. Also, those who want to learn a proven framework for developing viable AI products and network
- UI/UX Designers who are responsible for managing the user experience of AI-based applications
By Payal Mohta