The recent failure of IBM’s Project Debater in its contest against global debate champion Harish Natarajan offers the latest in a series of lessons learned about the deployment of natural language processing (NLP) technology in the real world. Project Debater is one of numerous attempts in a decades-old quest to use machines to automate the analysis of language to gather insights and make decisions.
“Hey Siri,” I said. “Call Nancy. Mobile.” Siri replied, “Calling Lindsay. Mobile.” It began to ring. I hadn’t worked with Lindsay in six years. I lunged for my phone and touched the red button just in time to avoid what would no doubt have been an awkward, out-of-the-blue conversation with her. Then, I contemplated the complexities of NLP development.
The release of two machine learning (ML) model builders have made it easier for software engineers to create and run ML models, even without specialized training.
Artificial intelligence (AI) is changing the way we work and live. At CloudFactory, our customers use data to train and optimize algorithms that power AI-powered products and services. We’ve worked on everything from AI for self-driving cars to political campaigns. Our work has shown us that the power of AI is limited only by the imagination of the humans who design the systems it powers.
The exponential growth of connectivity and technology are changing the workforce. The organization of the future is a “network of teams” connected by technology, but there’s a learning curve for executives on how to get there, according to Deloitte’s 2017 Global Human Capital Report. Most of the executives who responded to the survey pointed to building the organization of the future as the most important challenge for 2017. Yet, few are prepared to leverage the “new human models,” including contingent labor or outsourcing, that they’ll need to build it.
Experts disagree on where artificial intelligence (AI), automation, cloud computing, and machine learning are taking us in the future. And whether you believe machines will take over the world or that humans always will have control over technology, one thing is certain – we’re in for change.
Every Monday morning, CloudFactory hosts team meetings in each of our locations around the world: the U.S., UK, Nepal, and Kenya. Last week, our founder and CEO, Mark Sears, joined us from the UK to share a special message: Every single worker is important to our mission and, while it doesn’t always make good business sense to stop to assist someone else in need, it pays off in the long run by creating stronger relationships with CloudFactory workers and the people in our communities.
AI Creates New Jobs and Titles for Workers
If NASA’s recruitment for a planetary protection officer teaches us anything, it’s that interesting job titles are a sign of the times. We are just beginning to feel the impact of automation and artificial intelligence in the workplace, and we can expect that impact to grow as AI matures. Instead of being a job taker as many suspected, it’s shaping up to be a job creator.