April 1, 2016 | Written by: Gloria Lombardi
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Gloria Lombardi speaks with software startup advisor Steve Ardire to explore the state of Artificial Intelligence (AI) and its implications for the future of work.
In Part 1 of this post, we covered the meaning of AI vs. machine intelligence and how AI will affect the future of work. Now we turn our attention to what’s going on in the AI market and what this technology could mean for healthcare in particular.
AI technology is developing, fast. “In 2016,” Ardire says, “we are already seeing the emergence of applications for human resources, marketing and communications, sales, customer service, market and risk intelligence and more.”
The leading companies are pushing AI towards new horizons. Specifically, among the key trends is open-sourcing machine intelligence designs. For example, Facebook Big Sur, IBM System ML and now Open.
The rapidly emerging AI also includes many startups mostly currently flying under the radar. “AI startups have raised an aggregate of $967M in funding since 2010,” Ardire says. “And, the deal activity almost doubled in the last quarter only. Those investments went to companies in 13 countries and ten industries including business intelligence, e-commerce, and healthcare.”
Machine intelligence in healthcare
In fact, Ardire points to healthcare as one of the leaders in AI. A good example is MD Anderson Cancer Center. In 2014, the organisation started using Insights Fabric, a CognitiveScale-based platform, to improve patients’ experience, employee engagement, and enterprise operations.
Clinicians connect securely and privately with patients in real time. The health history of individuals is constantly updated as the smart technology learns and remembers people’s behaviours and preferences. This helps care givers to make personalised and tailored recommendations that are current, and to alert patients about key requirements precisely when they need it.
The future is unsupervised learning
But, reaching a state where organisations will be “machine intelligence literate” is not so easy. The majority of efforts today are still around “supervised learning,” where computers are given “training instances that are labelled with reinforcement,” According to Ardire. And training the machine takes time.
In addition, there is the challenge of embedding the technology into existing enterprise applications.
But, Ardire believes that machines will one day become intelligent systems just like the human brain. He says:
Going forward, the future is unsupervised learning where machines can infer what they don’t know about. They will be given no positive or negative reinforcement [by humans].
Indeed, it was Google Brain’s Jeff Dean who once explained, “Unsupervised learning is an important component in building really intelligent systems – if you look at how humans learn, it’s almost entirely unsupervised.”
If we think of the impact the internet has had over the last 25 years on the wider society, not least on businesses, it has been revolutionary. And, it has had some big implications for organisations and their workers. Now, AI is coming. In 25 years’ time might it have the same impact? Perhaps, the sooner we try to understand AI the better.