20 important takeaways for learning world from Mary Meeker's brilliant tech trends

Mary Meeker’s slide deck has a reputation of being the Delphic Oracle of tech. But, at 294 slides it’s a lot to take in. Don’t worry, I’ve been through them all. It has tons on economic stuff that is of marginal interest to education and training but there's plenty to to get our teeth into. We're not immune to tech trends, indeed we tend to follow in lock-step, just a bit later than everyone else. Among the data are lots of fascinating insights that point the way forward in terms of what we're likely to be doing over the next decade.
So here’s a really quick, top-end summary for folk in the learning game.

1. AI is getting bigger

Large tech companies see AI as their core strategy and enterprise spend on AI will increase. Google’s machine learning word recognition has just equalled human levels of accuracy. We can expect this to happen in the learning world with AI tools and services being used across the learning journey from engagement, support, chatbots, content creation, content curation, consolidation, assessment and wellbeing. For more detail see these AI in learning articles.

2. Employment flux

Technology is causing employment to change. Job roles are changing with more tech jobs but it looks as though unemployment is falling and that massive unemployment through tech is not happening, at least in the US. No need to panic – yet and be careful of hyperbole in this area.

3. Personalisation

This is getting ubiquitous online with Google, newfeeds, social media, music, movies, advertising, navigation, transport and buying online. It will happen in learning with everyone getting a unique learning experience that suits their needs and progress. Adaptive learning, based on individual and aggregated data, really does matter. There's lots of opportunities for personalised learning.

4. Data matters

Data matters but big data really matters. The problem in the learning world is that we have relatively small amounts of data at the user, course and institutional level. Expect data advantages to be leveraged elsewhere in online learning, on a greater scale.

5. Lifelong learning

Unusually there are five slides (232-236) devoted to Lifelong Learning. MOOCs continue to be popular, despite what critics claim. Top online courses, in general, are almost all in AI! 

6. Educational online ballooning

“Educational content usage online is ramping fast”with over 1 billion daily educational videos watched. There is evidence that use of the Internet for informal and formal learning is taking off.

7. Workplace learning and re-skilling getting big

Workforce online learning is getting big with increases in skills training and re-skilling. The need for skills training is rising along with employment needs, so workplace learning and re-skilling is increasing.

8. Voice the new UI

Voice is the new UI – Alexa led the way, so expect voice to become a way of interacting with learning materials. We’ve just completed a 100% voice led implementation of WildFire. The entire experience, navigation and voice interactions, means there’s no typing at all and there's lots of ways voice will change learning.

9. Messaging expanding

Messaging is going through the roof, so expect this to enter the learning game through more dialogue-like services. As learners use messaging as their primary way of communicating online, so this will be expected in online learning – hence the rise of the learning chatbot.

10. Chatbots

These are getting big. Increasing use in customer service is leading to their use elsewhere. There are many reasons to suppose that chatbots will be big in learning and lots of possible applications. They are already in the learning world, through Otto (Learning Pool), WildFire, Filter and others.

11. Video expanding

Use of video is increasing, as it will in learning. We can expect more adjunct products in learning around video, for example AI-created content produced automatically from video. We’ve been doing this with WildFire, where we use the automatically grabbed transcript and AI to create online learning, in minutes not months.

12. Workflow changing

Slack, Zoom and other tools transforming workflow and that is where learning and performance support has to be positioned, in those tools to catch people in the process of working, where they need help and support. Otto is a workflow chatbot that is integrated into many of these social platforms, accessible and on hand for performance support.

13. New content types emerging

Huge use of Twitch for watching games, signals new media types and genres. These could be used in learning. We will increasingly see messaging, chat, voice and other forms of UI enter the learning world.

14. Subscription service growth

People happy to pay subscriptions for services, as long as pricing is right. I can see this expanding in learning, especially on the use of smart, AI-like services, such as chatbots.

15. Big tech

Big Tech companies moving into new sectors – Google into retail, Amazon into advertising –  will continue and we can expect to see one of them move into the learning space some time soon. USA and China now the leading players. Europe’s role diminishing. My guess is that this will be on the back of the great strides they’re making on their core technical strategy - AI.

16. Tech saturation

As the world becomes saturated with mobile phones and other devices, sales growth is falling. They’re getting better, faster, smaller and cheaper. We can now get out of the ‘device-fetish’ era in learning and stop spending on devices to focus on services.

17. More online

People are spending more time online, up to 5.9 hours per day from 5.6 hours. If you want to get to learners you’ll increasingly find them online. This is borne out by the annual growth figures in online learning.

18. Physical retail sales declining

Physical retail sales de-accelerating as will physical delivery in classrooms, lecture theatres and training rooms. The pendulum swing to online will continue in retail and learning.

19. Privacy Paradox

As data becomes the new oil, oil leaks and spills also become a problem, so using data becomes more of a problem within the learning game. A curious but very real paradox. 

20. Warning for Europe

There’s an interesting little warning for Europe on slide 35, saying there’s a danger of unexpected consequences on too strict data regulation that restricts innovation and progress in Europe in particular. Interesting and, as you can see here, I agree.

10 fundamental ways voice recognition could change learning

‘Voice’ is one of Mary Meeker’s top five internet trends. Voice could be a game changer in interface behaviour, like keyboards, mice, joysticks and touch, but what impact could it have in learning?

Voice recognition, driven by leaps in AI performance, allows personalised voice recognition, even tonal and emotional recognition, and it is hands-free. It’s also low cost, requiring just a microphone and speaker and chimes with the rise of the Internet of Things. The three big barriers to adoption are accuracy, latency and social awkwardness.

Recognition and response must be accurate and fast. Failures and slow speeds turn users off. The good news is that we’ve punched through the 90% accuracy barrier and moving fast. At 95-99% (not easy) the show really is on the road. Already, the number of smartphone users using voice went over 60% in 2015 and that number is rising as the technology gets better and habits change. 

The uses, ranked, are; 1) General information (30%), 2) Personal assistant (27%), 3) Local information (22%), 4) Fun and entertainment (21%). An astonishing 1 in 5 searches on mobile in US (Android) are now by voice. But there are problems Meeker doesn’t mention. Sure we can speak (150 wpm) faster than we can type (40 wpm) but we can also read faster than we can hear. There’s also the huge embarrassment hurdle of speaking to non-humans in public spaces. She herself sees the initial impact in hands free environments – home (43%), car (36%), on the move (19%), at work (3%). This is when avoiding typing & menus, speed and convenience really matter. But in many other contexts, silence may remain golden.

AI driven voice

With Siri, Google Home and Amazon Echo, we see early signs of its power. Viv is coming and a slew of innovations in AI have improved its efficacy. Jeff Bezos thinks that AI will underpin tech for the foreseeable future. He goes further and thinks we currently understate its potential impact. Of course AI is not one thing, it is many very different things and voice recognition is just one of its many stunning applications. Sci-fi films have been showing us voice activated worlds for decades – it is now a reality. Natural language voice recognition, with the help of machine learning, has accelerated in just the last few years to become a mainstream consumer product.

Echo

Amazon’s Echo is a home-based, voice activated personal assistant, a competitor to Siri, using a platform called Alexa. Alexa has two software development kits; a voice service and a skills kit. As a customer, you get a weekly email telling you about these new skills (1000). This is a big push with over 1000 Amazon staff and tons of folk doing 3^rd party apps. It will play your music from Spotify, using just voice commands, even from the far side of the room when music is playing (clever), handle Google Calendar, read audiobooks, deliver news, sports results, weather, order a pizza, get a cab on Uber and control lights, switches, thermostats and so on. It is a frictionless interface to the ‘Internet of Things’. (An interesting tangent for voice activation is its use by those who are disabled.)

Above all, as a cloud-based AI service, on tap, learns fast and is always adapting to your speech, vocabulary and preferences. It becomes, in effect, a personal assistant that learns, not only about you but as an agent which also learns from aggregated data. This is where it gets interesting.
Enter Google Home, launched with new phones (Pixel) which activate the voice assistant when you switch them on. The aim is to get the Internet of Things going in the home through 'voice'- seamless music, activation of devices and ordering things.

Voice and learning

Google is great but we still largely write our requests. This is partly because it is quicker than speech. However, as speech recognition gets better, it will become quicker and easier to simply ask verbally. As Google Home, Amazon Echo, Siri and other services take many of us into the Internet of Things, in our homes, cars and other places, we will want voice to trigger events, get help, find answers and arrange our lives. The car is now a room, somewhere you can learn? The home is now networked, a place you can learn. Your mobile is voice ready, a place where you can learn. In some of these environments, having your hands free is essential (driving) and useful (home). How to tasks, like cooking, repairing things and finding things out make sense.

Behind this shift from text to voice is an interesting debate.
1. Speech is quick and easy
One could argue that it could push us towards more authentic, and I would argue, balanced, form of education and learning. Typing will always be an awkward interface. It is difficult to learn, error prone and requires physical input devices.
2. Listening is quick and easy
Reading is another skill that takes years to master. The spoken word is a skill we do not have to learn. We are grammatical geniuses aged three. Speech is primary and normal, reading and writing relatively recent adjuncts. So, when it comes to learning, speech recognition (output) and voice (input), gives us frictionless dialogue. It could stimulate a return to more Socratic forms of teaching and learning.

3. Less 'text' based learning
This may result in significant improvements in teaching and learning, both of which have, arguably, been over-colonised by ‘text’. Schooling, in all of its manifestations, has become ever more obsessed by text and there is a good argument for rebalancing the system away from an endless series of written tasks, essays and dissertations towards more efficient, meaningful and relevant teaching and learning.

4. Less text based teaching
The blackboard has a lot to not answer for. At that moment, teachers turned their backs on dialogue and conversation with learners and began to lecture, mediating their teaching with text, it can be even worse with text-laden PowerPoint. The teacher’s voice started to get lost. Nowhere was this more evident than in HE, where the blackboard reinforced and deeply embedded the ‘lecture’. To this day, especially in maths and sciences, ‘lecturers’ (a job title that uniquely identifies the profession’s problem), turned their back to learners and started writing. I, and millions of others, have endured the ‘three huge blackboard’ method of teaching. It is the opposite of teaching, it is writing. You may as well have emailed it to me.
5. Less text-based subjects
In schooling we also had the drift towards text-based subjects. Latin is the most surreal example, a dead language, no longer spoken, no longer even written, taught for no other reason than the fact that it got embedded in the curriculum. What a waste. Shakespeare, largely taught off the page, killing it stone dead for many who should have been excited by its searing effect when spoken on the stage. The obsession with ‘maths’, in slavish adherence to PISA, which was never their intention, is also made easier by its essentially written nature.
6. Less text-based assessment

The essay as assessment has now descended into a game where students know that they will not get feedback for days, even weeks (often a grade with a few skimpy comments). So they share, plagiarise, buy essays and in exams, memorise them, so that critical thinking is abandoned in favour of regurgitation. This is not to argue for the abandonment of writing, or essays, just less dependence on this one-size-fits-all form of assessment.
We have a system that teaches to the text and the tests of the text. Almost everything we test is in the form of the written word. Oral and social skills count for little in education. Practical skills are shoved below stairs and we send our kids off in lock-step to universities where the process is extended for year after year, often an inefficient and expensive paper trail that results in a huge paper IOU for the student and state.
7. Less focus on paper outputs

In my lifetime I have seen HE morph into a global paper farm, with exponential growth of Journals and text output, matched only by the inverse growth in readers. Research is falsely equated with paper output, where the paper is the end-in-itself. Teaching is often side-lined as this paper mill becomes the dominant goal.

In the professions, and especially in institutions, I have witnessed bureaucratic systems whose function is often to simply to produce ‘reports’. These are invariably overwritten, skimmed, then often binned. Report writing, plans and rhetoric are so often substitutes for action. Nowhere is this more apparent in the report than invariably conclude that “more research is needed in…”. Reports beget reports.

8. Less long-form output
In a way I think the historic, educational obsession with long-form text has been saved by the internet, where writing returned to a broader set of forms. Young people have taken to writing like demons, in txts, messages, posts, Tweets and blogs. There has been a renaissance of writing, reflecting a wide set of forms of communication, supplemented by images and video.

So how will voice manifest itself in learning?
9. Rebalance academic and skills
It may also help redress the balance between the academic and vocational. When learners leave the confines of school, college or university, they by and large have to exercise skills that are oral - dealing with work colleagues,  interacting in meetings, being effective on the phone, dealing with customers and so on. You will spend a lot of time speaking and listening - these become primary activities and skills. These are not skills that are taught in many educational institutions. A return to voice-based learning may help here.
10. More dialogue
Dialogue with smart people on any topic is often a powerful form of learning. They challenge, probe, contradict. This type of collaborative learning may come into its own with speech and dialogue. There is also the sense in which some topics benefit from the lack of images and writing. It allows the imagination to construct personal imagery and links to what is being heard.
Adaptive learning, intelligent tutoring, chatbots… all of these are with us now. This form of technology enhanced teaching can be further enhanced with voice recognition and feedback. One can see how AI, adaptive, tutoring software could turn this, first into a homework support tool, then a tutoring tool, through to the delivery of more sophisticated learning. It has the advantage of being able to both push and pull learning. I like this idea of encouraging habitual learning, the delivery of short questions, quizzes and spaced practice, via voice on the echo, in a personalised sequence. In the privacy of your own home, this takes away the public embarrassment factor.

Voice moves us one step closer to frictionless, anywhere, anytime learning. Places other than institutions and classrooms become learning spaces. The classroom and lecture hall were never the places where the majority of learning took place. Context matters and as learning becomes a utility, like water, we ill be able to call upon it at any time and see learning as habitual and informal, not timetabled and formal.

Conclusion

I am not denigrating the written word. It matters. What matters more is a rebalance in education towards knowledge and skills that are not wholly text-based, but recognise that speech is as important, sometimes more important, and that skills also matter. Imagine a world where the only response to a request or problem is… I’ll write that up. That’s a problem. Education in its current form is not the solution to that problem but part of the problem itself.

Voice is here - online learning has been traditionally 'nil by mouth' but not now....

Curious conundrum - nil by mouth

Online learning needs to be unmuted. Almost all online learning involves just clicking. Not even typing stuff in, just clicking. We click to navigate, click on menus, click (absurdly) on people to get fictional speech bubbles, click on multiple-choice options. Yet most other online activity involves messaging, typing what you think on social media and being far more active. Also, in real life, we don’t click, we speak and listen. Most actual teaching and training uses voice.

Voice is our first and most natural form of communication. We’ve evolved to speak and listen, grammatical geniuses aged three and are not in any formal sense, ‘taught’ to talk and hear. Whereas it takes many years to learn how to read and write and many struggle, some never achieving mastery in a lifetime. Is 'voice' a solution?

Rise of voice

Strangely enough we may be going back to the pre-literate age with technology, back to this almost frictionless form of interface. It started with services such as Siri and Cortana on our phones. As the AI technology behind these services improved, it was not Apple or Microsoft that took it to consumers, but Amazon and Google, with Alexa and Google Home. I have an Alexa which switches my lights on and off, activates my robot vacuum cleaner, plays all of my music and smart TV. I use it to set timers for calls and Skype meetings. We even use it to voice message across the three floors of our house and my son who lives elsewhere. I use it for weather, news, sports results. In Berlin recently, with my son, who has Bluetooth headphones linked to Google Assistant, he wanted a coffee and simply asked where the nearest coffee shop was and it spoke back, giving voiced directions as we walked. Voice is also in our cars, as we can speak commands or get spoken to from Google Maps. Voice is c creeping in everywhere.

This month we’ve also seen tools emerge that analyse your voice in terms of mood and tone, and also evidence that you can diagnose Dementia, Parkinson’s and other illnesses from frequency level analysis. As Mary Meeker’s analysis shows, voice is here to stay and has become the way we interact with the internet of things (IoT).

Voice for learning

1. Voice as a skill

Text-based learning has squeezed out the skills of oration, yet speaking fluently, explaining, presenting, giving feedback, interviewing, managing, critical thinking, problem solving, team working and much of what is called 21^stC skills, are actually skills we used to teach more widely through voice. They are skills that are fundamentally expressed as speech, that most fundamental of media. People have to learn to both speak up and when they speak, speak wisely and to good effect. It is also important, of course, to listen. For these reasons, the return of voice to learning is a good thing. Speaking to a computer, I suspect, also results in more transfer, especially if, in the real world, you are expected to articulate things in meetings or in the workplace to your colleagues, face to face.
2. Podcasts

Another sign that voice is an important medium in itself are podcasts, which have surprised people with their popularity. This is an excellent post on that subject by Steve Rayson. The book  “Podcasting: New Aural Cultures and Digital Media’ by Llinares, Fox and Berry (2018) is an in-depth look at the strengths of voice-only media; the ability to listen when you want (timeshift), use when walking, running, exercising and driving, long pieces having more depth often with multiple participants. In addition, they make you feel as though you are there in the conversation with a sense of intimacy, as this is ‘listening’ not just ‘hearing’, especially when wearing headphones. Podcasts should be used more in learning. 

3. Podcasts and online learning

We’ve been using podcasts in WildFire. One real example is a Senior Clinician, who ran and authored a globally significant medical trial in Asthma. We allow the learner to listen intently to the podcast (an interview) then grab the transcript (automatically translated into text) to produce a more active and effortful learning experience, with free text input. You get the best of both worlds, an intimate and reflective experience with the expert, as if you were there with him, then you reflect, retrieve, retain and can recall what you need to learn. Note that the ‘need to know’ stuff is not every single word, but the useful points about the scale of the trial, it’s objectives and findings.

4. Text to speech

We’ve also used AI, text to speech, to create introductions to online courses, making them more accessible and human. The basic text file can be edited at any time, with ease, if it needs to be changed. These audio introductions have been used in Train the trainer course and a course fo a major Hotel Chain, where learners may need something more than pure text and images.

5. Voice input

We’ve also developed voice-input online learning, where you don’t type in answers but ‘voice’ them in. This is a very different cognitive and learning experience from just clicking on multiple-choice options. Our memories recall what you think you know in your phonological loop, a sort of inner ear where sounds are recalled and rehearsed before being either spoken or written. This is the precursor to expression. Voicing your input jut seems more like real and not artificial dialogue. The entire learning experience is voiced, navigation and retrieval with open input. This, we believe ,will be useful for certain types of learning, especially with audiences that have problems with typing, literacy or dyslexia. Voice is starting to creep into online learning. It will grow further.

6. VR

One of the problems in VR is the inability to type and click on anything. Put on a headset, and typing when possible is far too slow and clumsy. It is much more convenient, and natural, to speak within that immersive world. This opens up the possibility of more flexible learning within VR. Many knowledge components, decisions or communications within the simulation can be voiced as they would be in the real world. Voice will therefore enable more simulation training.

7. Feedback

Voiced feedback is used by some, obviously in coaching and mentoring, but also in feedback to students about assignments. The ease of recording, along with the higher impact on the learner in terms of perceived interest by the teacher, makes this a powerful feedback method.

8. Assessment

So much learning is text based when so much of the real world is voice based. Spoken assessment is, of course, normal in language training but shouldn’t we be expected to voice our opinions, even voice critical pieces for assessment. It is relatively rare to have oral examinations but this may be desirable if newer softer skills are in demand.
9. Chatbots
Voice interfaces with chatbots have been launched on home devices such as Alexa but we will see domain-specific chat emerge. Google Duplex was the first real showcasing of a conversations sensitive product that can actually make voice calls to a restaurant or hairdresser to make appointments. This is not easy and on limited release. But it is a sign of things to come - more prolonged dialogue by voice.
10. Voice agents
Learning techniques such as mentoring, coaching and counselling will, in time, benefit from this voiced approach. Trials with CBT counselling bots have shown promising results in clinical trials and the anonymity, even the fact that it is NOT human, has proven to be rather counterintuitive advantage.
Conclusion

Online learning needs to pay attention to AI-driven voice. It is an underlying consumer technology, now ubiquitous on phones and increasingly in our homes. It is natural, convenient, intimate and human. It has, when used wisely, the ability to lift online learning out of the text and click model in all sorts of imaginative ways.