Smart agents are already being built by small companies. Soundhound, for example, started as a very small technical team that built a fantastic mobile smart agent, Hound, for song identification, and they are now going after very big markets with their agent technology. Even open source agents, like Mycroft.ai are in early development.

A single scrum team (seven plus or minus two) can presently stand up, sell, and iterate a simpler agent, and bot frameworks from Microsoft, Facebook and others are rolling out right now, so this is a great time for entrepreneurs to find the pain points that agents can uniquely solve today.

Audio Augmented Reality

Augmented reality (AR) will be a key knowledge base — and interface — in the coming web. We’ll explore the future of AR in our next post, but let’s just say a little about the audio component of it now.

I expect our PAIs will begin to listen in on our lives in realtime at some point during in the (late?) 2020’s, recording just our side of our conversations (an easy technical feat), and those of any others we have permissioned from, in our personal knowledge bases. PAIs will use that continuous textual data (a trivial amount of storage) to keep improving their personalized knowledge of us. They’ll be able to use this data, and their growing general knowledge, to whisper into our ears during our conversations via audio AR, just like Samantha in the brilliant sci-fi film Her (2013). You might be surprised to discover how useful these abilities will make them, even long before they have any kind of higher neural-network based intelligence.

The smart agent Samantha, speaking to Theodore Twombly (Joaquin Phoenix) in Her (2013)

I once heard a claim, from a computational linguist whose name escapes me, that if you have two years of recorded conversation of a typical user, even with non-deep learning based (statistical) NLU, your natural language model will be able to predict with up to 80% accuracy, the word they are struggling to say next if they are having a tip-of-the-tongue experience (“senior moment”). One year isn’t a complete enough conversational map of our common sayings, but two is, and it presumably gets even a bit better from there over time, at least for adults, who learn much less rapidly than children. Will our deep learning-backed PAIs be able to whisper those completion words in many folk’s aging ears in the 2030s? Will many seniors enable this feature? I would bet they will, even though it will be creepy at first.

Egro’s Bluetooth Earbud, $13. Courtesy @lifeofc and John Li

Long before this, we will use audio AR, and secondarily, visual AR, as a very efficient and natural way of interacting with each other and our PAIs while doing things in the world. See John Li’s great Medium post, “What if the Future of Technology is in Your Ear?” 4.22.16 for a similar view. Li’s post reminds us it is simply an oversight — a lack of vision — that no smartphone maker has yet developed a magnetically docking and autocharging mini-earpiece that is integrated into the ends of our phones (and will beep if it gets too far away from the phone) so we don’t have to keep track of them. They can make big bulbous ones for parents with small children at home (a choking hazard) and little ones, like this one here, for the rest of us. Dear engineers, please deliver this to us. It’s overdue!

From Apps to Operating Systems

I hope this background convinces you that PAIs and their knowledge bases and hardware may begin as apps, from the developer perspective, but the smarter they get, the more attached to them we’ll become. I think we’ll eventually come to see them as much more like operating systems. Like our smartphones today, we’ll think of them as the new root-level hardware and software mediating the interface between us and the world.

As our PAIs get to know us and “test” us conversationally, and gain the ability to update their models based on our responses (a capacity AI developers have yet to add), they’ll increasingly advise us on how to best interact with others, how to work well in teams, who to associate with, how to learn new skills, which skills are most marketable given our current skills, how improve our health and performance, and even what to invest in, how to vote, and what political actions are in our best interests.

People who use, talk to, and train their PAIs well will be increasingly better off than than those who don’t. If this vision comes true, the use and deployment of increasingly smart agents of all types will be central to individual, team, and organizational strategy and competitiveness.

The Quest for Lock-In

Big companies will spend fortunes on agents in pursuit of consumer lock-in with bots, agents, and PAIs. Some of this lock-in should even be more economically valuable than previous lock-ins. But at the same time, the smarter our agents get, the easier switching will be, even for highly personalized AIs. There will always be an agent retraining cost, in time and money, but the wealthier society gets, as we’ll see in our PAI economics section, the more users will value other things besides just having the fastest and smartest PAIs on the block.

So as their smartness grows, we will argue that the IT platform “lock-in” that occurs with PAIs is likely to be even lower than we’ve seen with every antecedent IT platform (operating systems, social networks, ecommerce and entertainment platforms) to date. We had lock-in for a couple of decades with Microsoft Windows on our desktops, but eventually Apple’s iOS, Linux, Android, etc. also emerged as viable alternatives. Alternatives will emerge even faster in the world of PAIs.

Basic Income, PAI Trust, and Open Source

Eventually, our PAIs will get smart enough to show us the benefits of voting in basic income to combat ever-accelerating technological unemployment, a coming form of personal empowerment and one of the big topics we’ll discuss in this series.

Read Brynjolffson and McAfee’s excellent The Second Machine Age (2014) for more on basic income. Consider how PAIs that can lobby for us, when combined with disappearing population growth and accelerating technical productivity, will make a basic income inevitable in coming years, in every country still based on one person, one vote. Of course, just because it’s inevitable doesn’t mean it will arrive in a timely manner, or in the most socially empowering way.

If we give out income at too high a level, too suddenly, and without incentives to personal growth, we can take away personal incentive to work, as we see in dependency economies like Saudi Arabia. If we aren’t fiscally responsible, we can also drive our country to insolvency with benefit bloat as in Spain, Greece, and other countries where leaders have grown benefits faster than technical productivity. So there are lots of ways to mess up a basic income. But lots of evidence, including Canada’s Mincome experiment, and income incentives like the U.S. GI Bill, have shown it can be greatly socially empowering as well. I’m personally convinced that lobby PAIs will play a key role in bringing it about, as we will discuss in a later post. So let’s make it happen well.

Because the trust we need to have with our PAIs will grow as direct function of their power and intimacy, there will always be a core of users, from the very beginning, who find open source PAIs a more desirable, and controllable solution than proprietary alternatives. I’m sure a few open source PAI projects will gain the kind of traction that Linux gained with developers in the 1990s. As the technologies behind PAIs get commoditized, and once basic income rolls out, open source PAIs seem likely to be particularly powerful, serving a major role in keeping proprietary PAIs honest and reasonably priced, just as open source does with existing commercial software today.

Consider that once we have a basic income, the need for any of us to have a PAI that can outcompete our neighbor’s PAI becomes far less compelling than it is today. Eventually, the need to have the “best PAI on the block” will be as uninteresting to most of us as having the “best desktop on the block” has become today. Even just five years ago, when processors weren’t that powerful, desktop computer performance was still a “thing”. At a certain point, the average 21st citizen will have enough personal technical capacity, with their agents and home automation, enough financial savvy, with PAIs smart enough to help them live within their means, and enough social equity, with basic income and the sharing economy, to cover their living essentials. In that world, our values will change, and agent trust, personalization, and trainability will be key. We’ll be less inclined than ever to use agents whose loyalties we suspect are divided between the interests of its makers and our own, even if that gets us additional personal competitiveness.

Meanwhile, we have a long road to a basic income society. On the way there, control over our PAIs private data will be a right we all have in principle, though the extent to which we exercise that right remains to be seen. The ability to export our private data, to contest and correct public data, may be the greatest extent of data control that the average citizen ever gets. In the coming world, what matters most to us, I believe, is not democratic control over big data, which may remain unreachable, but control over our most intimate algorithmic interface to the world, our personal AI.

Our Next Post

In Part 3, The Agent Environment, we explore the accelerating arrival of mediated reality, the virtual component of the knowledge web, and a few of its many implications for agent evolution and development.

Calls to Action

If you’d like an email reminder on this series, enter your email address to get our newsletter, Accelerating Times.

Consider making Reddit Futurology your homepage. They’ve got 6M+ “Futurists” now. It’s now a great open discussion space for what’s next.

If you know an agent resource that should join this story, please let me know (john@foresightU.com) and I may share it in future posts.

Thanks for reading!