“Software is eating the world.” Marc Andreessen spoke true as tech startups upended traditional companies in every industry. Even now old corporations struggle as technology continues to improve and advance, and the threat of disruption is everywhere. No where is that more felt than those who worked in blue collar industries, where many suddenly found themselves out of a job, replaced by machines and software. It was not a pleasant feeling, and with the inevitable advent of AI, even white collar jobs have reason to be concerned.For a long time many people in industries like consulting, accounting, or law felt that software could never replace them. The ability to problem solve and develop human relationships was something many felt software could never do. AI is different though. AI is built with the intent of bridging gap, training a program to come up with it’s own insights and to be able to think proactively. If these predictions turn out to be true, many industries people believe to once be untouchable by technology, may not be so untouchable after all.
However, many people believe there is no cause to be worried such as Bridget Karlin, CTO and VP of IBM’s Global Technology services, who heads IBM Watson, an AI platform for business. Built on the cloud and used for looking at data, understanding, reasoning, and learning from it, IBM Watson gained prominence after beat two renowned Jeopardy winners. It was considered to be one of the best use cases of AI, and is currently used as a platform for business.
For Bridget, AI is a significant market opportunity that will augment humans, help them better solve problems, and open up new career opportunities. To make her point, Bridget cites a use case of IBM Watson, where a 66 year old woman was diagnosed with leukemia. Doctors put her through chemotherapy, yet despite the treatment the woman only got worse. They then brought in IBM Watson, and after filtering all the test data into the machine, within 10 minutes the system discovered that the woman had a different strain of leukemia and therefore required a different treatment.
And IBM is not the only player to see AI as a new market opportunity. Nvidia has been increasing its efforts in the AI space, creating both the hardware and the software to create more accurate AI programs. Moreover, they have been heavily involved with their partner GE, who often bring products to hospitals. Almost 50,000 terabytes of data is produced within hospitals using Nvidia’s hardware, although 90% of the data isn’t processed. However, the company hopes to use the data and derive insight from them, helping to speed transaction times and learn to identify diseases and diagnose them earlier. Furthermore, with data from government and industry, Bridget and Ned both agree that the chance to predict natural disasters could be possible with a well-trained AI Program.
Now, although the potential for AI is huge, historically disruption, especially through the tech world has caused people jobs. Although there is a belief in economics that although emerging technologies eliminate jobs, they often bring in new ones, the caliber and technical sophistication of the jobs grew. It wasn’t easy to make a rapid career change or in the case of traditional businesses, to suddenly digitize. In terms of how to navigate the new advent of AI, the National Telecommunications and Information Administration (NTIA) has some thoughts on that.
The NTIA is not a regulatory agency but rather serves as an advisor on emerging technologies and how the government and the rest of the US ensure that emerging technologies benefit all Americans, not just a select few. Over the past couple of year, people in the agency like Deputy Associate Administrator Evelyn Remaley have been studying the different aspects of AI, trying to understand the technology and how to best position themselves to optimize the technology for both the public and private sector.
While studying this phenomenon, they’ve asked themselves questions such as what best practices should be developed for the new industry and what commitments can made to address issues such as job displacement or cybersecurity. Evelyn believes some ideas floating around are multi-state quarter policy processes, processes that will bring both civil society and industry together to help develop products that are safe, affordable, and competitive to the US. They also encourage policy makers to educate themselves on all aspect of AI and support public and private partnerships that use AI in a positive way. As it becomes more and more apparent in the business world, she states it is important for agencies like the NTIA and those in Washington to be fully versed in the industry. This will be done to ensure that companies remain competitive but to also ensure that the government does not unfairly regulate the businesses that use AI in a business friendly way.
Evelyn does make it clear though that tech companies and those working on AI are responsible for guiding the development in a responsible and ethical way, ensuring that there are safeguards when AI programs are trained and protected from issues like bias. She and the NTIA have published 4 principles that should be observed when it comes to the development and uses of AI:
AI must always augment human intelligence, with an emphasis that AI is used to help make humans smarter and better.
There must be transparency within the industry, where AI is being applied and what data is being used is something that should be public knowledge
Application and data usage must be public, but data and insights from AI processes stay with clients. Essentially, as Enterprise businesses gather data and derive insights through their AI programs, the data they gather, fundamentally, though belongs to their customers.
There must be an industry commitment to helping students and workers at large develop skills necessary to succeed in this new industry.
Principle number 4 is something Evelyn emphasizes, as those employees are living in a time when things are moving even faster than before. She recommends policies such as apprenticeships, helping people re-skill and relearn to get new jobs, as opportunities to help bring new jobs and opportunities in the AI space, and ensuring workers have the skills to take advantage of such jobs.
Companies like IBM and Nvidia have done well to follow these 4 principles, according to Bridget from IBM Watson and Ned Finkle, VP of External Affairs at Nvidia. According to Bridget, the biggest users of IBM Watson is IBM themselves, where they have developed as service platform to derive insights from operational data to help with their business. One example is with their IT infrastructure, where they combine analytics with automation to keep in healthy and functional. In addition, they use it to predict incidents and catch issues within the company and with clients. One such issue is the cybersecurity industry. As the world gets more and more connected and features like privacy and data become more vulnerable, AI can be used to not only observe malicious activity but also come up with potential solution to deal with such issues.
In order for this happen successfully though, Bridget emphasizes the the industry and government need to come together. The advent of AI is to great a problem for either party to solve on their own, and she states it is their responsibility to come up with an ecosystem that ensures the marketplace is fairly and securely using data, creating competitive AI products that augment humans, and providing a solution to employees who will be disrupted by this new technology.
IBM is already making steps to help educate and train the future workforce through their program called PTECH. This program allows high school students to gain a diploma, with no cost to parents and even allows them to get a job right after graduation. Bridget claims they have about 50,000 kids going through the program and will help fill the shortage of roles, such as those who need to train AI systems to make them smarter, and those who will explain the insights and verify the correct use cases of data by AI programs.
Nvidia, on the other side, is working to create partnerships with colleges and employers around the country help prepare them for the “new collar industry.” Surprisingly, Ned states that there is a shortage of data scientists at Nvidia, providing incentive for the company to invest in the education of new talent.
As the companies continue to advance their AI programs and make advances in the industry, government and businesses will continue to determine how best to bring all perspectives to the table. One such perspective involves the access of Big Data. Data is essential for AI, the question of how companies will use it without compromising its integrity is a big topic. As companies feed more and more data into their AI programs, their data will become their competitive advantage. But that is not the only concern. A executive order was issued which found that the incentives in the marketplace weren’t always properly aligned to promote issues like security and privacy. As each company attempts to work the fastest to get the best AI products into market, security may not be their priority, which is something Eveyln states must change.
It is clear though that the AI revolution is coming whether we like it or not. Whether the disruption will be good or bad and who ultimately benefits or not will ultimately be determined by the ecosystem private business and government decide to create.