As a VC, I’ve been researching and tracking technologies broadly within the “Future of Work” space. Ask any VC and you’ll get different responses as to what Future of Work covers — be it collaboration, productivity, AR/VR, RPA, and more. So I thought I’d share some of our early learnings at Work-Bench, which are ever-evolving — we’d love to hear from you, and to continue to learn.
I was recently invited to join a great panel hosted by New America NYC, on the theme of Future of Work, featuring Rick Wartzman’s new book: The End of Loyalty: The Rise and Fall of Good Jobs in America.
We covered a wide swath of topics that surrounds this complex issue: the decline of unions, depressed wages, education, healthcare, the changing role of employers’ responsibilities.
I talked about the unique confluence of my own personal perspectives — as VC investing in technologies that are disrupting and transforming work; as a long-time GED educator, teaching at the 1199 SEIU Labor Union; advising LaGuardia Community College on student and workforce development initiatives; and even formerly having worked at Cisco Systems within their Learning and Development (corporate training) team.
Where I spend a lot of time thinking about at Work-Bench is this theme of human-centered AI.
Amidst the doom and gloom that AI and machines will take away our jobs…there will be some period of time when data platforms can help enable and augment humans: to be more efficient and effective. To do our jobs better, faster, and happier. And/or to free us up to do work that is more complex, creative, compelling.
How can we ensure AI is built with a human-centered and empathic approach? Where we are not trying to remove or automate away the human, but rather, use their input and knowledge to better train the AI systems and models; to unlock and enhance our human abilities to make otherwise inaccessible data-driven actions and decisions; and to be developed with the expertise, experiences, and insights of humans in mind?
In all data there is humanity . In every bit there are traces of of this humanity: in how a choice is made, or how a system is built. In the physical world the complexities of this humanity are magnified. To manage this complexity requires both deep technical expertise and innovative engineering. It also requires considerable empathy for the human beings behind that data.
Those of us who work with data are fond of describing it as messy, but data from the physical world is more than simply messy. It is knotted up in the perpetually flawed mechanism used to convert analog actions to digital signal, and the humanity that underlies it. The complexity of this humanity, however, is also our greatest strength and opportunity. The expertise, experience, and bias that people imprint on the data provide material for building great products.
Some examples of startups helping to remove really painful, repetitive, and manual work:
- Upskill — smart glass wearable solution that helps line technicians better assemble complex manufacturing parts through their hands-free, voice command viewfinder (and literally removes painful repetitive motion: https://upskill.io/landing/upskill-and-boeing/)
- x.ai — virtual assistant who helps remove the pain of scheduling (and rescheduling) meetings
Some great examples of software augmenting humans to do their jobs better:
- Alluvium — helps enable industrial operators by providing more data and insights around production stability
- Merlon Intelligence — helps compliance analysts more effectively monitor transactions for money laundering by surfacing suspicious activity
Do you know other companies in this space using a human-centered approach to building AI, data analytics, and automation? I’d love to chat.
*All of the above companies are Work-Bench portfolio companies.