AI could help us be better humans

People often say that we humans needn’t worry about growing automation, that what we should do is just focus on the things that humans do best: things like empathy and interpersonal communication. But does that really seem like a long-term defensible competitive advantage over the robot co-worker who would steal your job? I don’t think so.

What if it wasn’t about stealing your job, though? What if it was about using AI to make you a better person. Like, more honest, more co-operative, more considerate? The world could really use a lot more of that.

As Microsoft’s Dr. Ece Kamar said in a great recent interview, quoting her PhD advisor Barbara Grosz, “We already know how to replicate human intelligence: we have babies. So, let’s look for what can augment human intelligence, what can make human intelligence better.”

Two new studies written up at Kurzweil AI today demonstrate powerful and fascinating ways that humans and computers could work together for mutual benefit.

The first is a study of an algorithm that plays games with humans and seems to be able to get humans to be more co-operative by goofing around with them. The system uses “cheap talk (i.e., costless, non-binding signals)” between games and saw human opponents willing to co-operate more as a result. Is that a computer teaching us how to be better humans? I think it may be. And if you don’t co-operate? Then you get an electric shock! Just kidding, that was not part of the study. Coercion vs incentivization and behavior modeling seems a big important distinction though. I don’t want a bot threatening me into being more cooperative, but this study seems to demonstrate that if you want humans to play nicer, you don’t have to be coercive – you just have to play it cool.

Part of being human, of course, is learning and being wrong sometimes. As Microsoft’s Kamar points out, though, AI and machines are often wrong too- they have big blind spots just like us humans, only in their case it’s our blind spots that define theirs.

The second study cited by Kurzweil AI is of a beautiful system described as “A Crowd-powered Conversational Assistant Built to Automate Itself Over Time.” This one was built by a team that included crowdsourcing community leader Jeff Bigham (the second most influential Jeff in the crowdsourcing community) and it’s a swoon-worthy system of collaboration between multiple chatbots and Mechanical Turk. The Turk workers are asked for answers to users’ questions, then they vote on the best answers, and the best answers are added to the meta-bot’s library of answers for next time.


Bots making humans better humans, and humans making bots better bots. That’s a vision of the future I can get behind.

Digital Transformation: Data is not the most important part

People have been saying for years that “data is the new oil” – but oil needs an engine. That analogy may break down, too, if data isn’t scarce but great engines are.

Analyst firm IDC released a series of reports on four parts of digital transformation yesterday and it could be looked at that way. I haven’t read it in full but I love the way it’s laid out and really appreciate that we’ve come to a place in history where this kind of model is valued as an asset.

Central to this model is not data, but an “intelligent core” that processes internal and external data.

The model here, in narrative terms, is this: digital transformation is a cyclical process that runs internal engagements like data from instrumentation and insights from people, processes, assets and APIs, as well as external engagements like shared data and actions taken, through a central intelligent core. What’s in the core? Developer services so internal and external data can be worked with, and an orchestration layer to make sure everything keeps operating smoothly.

As data churns through that intelligent core, being processed by developers and being kept in sync with orchestrated processes, then it goes back out of the core into internal and external engagement, as new insights gleaned and new actions taken.

As I’m writing this, I’m in transit to visit a customer for which Sprinklr could totally be understood as providing the intelligent core for a substantial amount of this kind of digital transformation.

In this model, the data is important but the intelligent core is where the leverage comes in. IDC’s announcement quotes Meredith Whalen, senior vice president, thusly: “What is important to take away is that the data does not distinguish the company. It is what the company does with the data that distinguishes itself. How you build your intelligent core will determine your potential as an organization.”

That brings to mind something Jack Clark of OpenAI said on Twitter recently. He criticized the outdated belief that “Data is the most strategic thing” and argued instead that “compute is the most strategic thing. In the future we’re going to be using procedural environments/complex game simulations, so you get the data from your simulator and the strategic point comes from using compute to run it faster (aka generating more data). Another way to think about this is the rise of GAN [Generative Adversarial Network] techniques for data augmentation – you sample a distribution of initial data then you use compute to massively expand the available data via GANs, or whatever. Ultimately, compute trumps data.”

That’s probably taking it to a whole new level – arguing that the core could use AI techniques like Generative Adversarial Network AI to take a little bit of data and extrapolate out to build far more data to capture insights from. That’s cool to imagine.

Exciting times!

Digital Transformation will change how we work and live together

I was asked in an interview that I hope will appear online soon what I’m excited about that’s coming in the future of social media. Based on some thoughts from Dion Hinchcliffe that I wrote about recently and some historical context from Andrew McAfee and Erik Brynjolfsson’s new book Machine, Platform, Crowd: Harnessing Our Digital Future, here is what I wrote:

In short, I’m excited about how social media is changing the way we work. I’m excited about the coming bounty of real understanding and increased humanity that I expect to be a part of digital transformation. 20 years ago, the digital re-engineering of the enterprise brought new levels of efficiency and freed many people from their most repetitive work. Now our jobs require far more creativity, self-determination, communication, and other fundamentally human skills.

That type of transition is underway again in what we call Digital Transformation. Now it’s new technologies like social networks – both inside and outside of enterprises, new ways of working like the practice called “working out loud,” and new, network-informed ways of thinking about stakeholders, measurement, growth and management. This is an exciting time, this time of the consumerization of the enterprise. Hopefully the enterprise will have a lot to add to the mix as well – and the new capabilities of social media will be leveraged in powerful and positive ways at work.

On a deeper level, below this question about work, I’m excited about the ongoing democratization of communication and self-awareness that social media offers. It continues to face criticism, for example recently from some of the people who helped create it, as “short-term, dopamine-driven feedback loops we’ve created [that] are destroying how society works.” But I think that’s just a sign that we as individual participants need to take more responsibility and use social media more effectively. History will be the result of both structural and macroeconomic trends and our individual decisions, together.

Aiming for Goldilocks-level innovation

“We want to reinvent, but we sure … don’t want to reinvent the wheel.” – Warby Parker co-founder Neil Blumenthal.

That line really struck me from this Fast Company article “The Future of Retail in the Age of Amazon.”

It reminded me of my friend Hideshi Hamaguchi‘s analysis of innovative products in terms of new and known behavior and value.

Hideshi explained that creating a product that allowed users to capture new value from known behaviors is a great way to make something attractive and comprehensible for the market. Making something that enables users to capture known forms of value using new (hopefully simpler) forms of behavior is good too. But when you’re innovating in terms of both behavior required and the form of value that comes from it – that’s going to be a tough sell.

I made a crude visual representation of that here. Hideshi’s would be much more attractive, I’m sure. In this case Green certainly doesn’t mean “go.” It just means, this is the easiest path to go to market. The yellow quadrants are probably the smartest way to successfully innovate.

This was a big struggle in building Little Bird, before it was acquired by Sprinklr last year. We were in that top right red quadrant. We were asking users to set up workflow systems to regularly check in on and engage with content highlights from high-impact people, on any topic, not filtered by keyword, in order to find key opportunities in a cloud of conversation to co-create value as a part of. That’s pretty awesome, but for most people it’s new behavior to capture new value.

Thankfully, now that we’re part of Sprinklr, the data we surface is much more easily actionable through more familiar behavior and delivers more familiar value.

One of the mistakes I made was building in that top right corner. The company could have been much more commercially compelling on its own if we’d succeeded in moving toward the more-popularly known axis in one direction or another. We knew this, I was just stubborn. )And it’s much easier said than done – we certainly tried.) I’m stubborn in large part because I am motivated more than anything else by awe, and the abundance of opportunities I personally have always been able to create with the behavior and value exactly as we delivered it was (and is) something I’m in awe of. In the future I’ll team up, with greater self-awareness all around, with settlers I can pass the ball to. That would probably be necessary but not sufficient.

Word to the wise!