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.

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.

Talk To Me by James Vlahos; great read for those working in or interested in bots...

We have Alexa in three rooms in our house – living room, kitchen and bedroom and they’re all used every day. I use it for work (calculations for VAT, invoices, scheduling), cooking (timers), shopping (lists), lights (off at night), robot vacuum cleaner and lots of queries. Google Assistant on my Pixel phone is now my PA. Voice, through use and habit, has become part of my life – my frictionless interface – easy and convenient. 

As one of the great triumphs of AI voice is on our phones, in our cars and in our homes. Amazon, Google, Microsoft and Apple all see it as a strategic technological advance. We take years learning how to read and write, yet we listen and speak almost effortlessly, grammatical geniuses aged three.

So it was great to come across a readable book that dealt with the territory to date. The history of voice and chatbots is well covered as it did not spring out of nowhere but from centuries of maths, statistics and probability theory, then pioneers who applied the maths, and AI, to the recognition, understanding and generation of language and voice.

Vlahos explains why all the moral hysteria around the gender of voice assistants is misplaced. Far from being a patriarchal plot; Siri, Cortana, Alexa and Google Assistant were all extensively researched and all but one give users the choice of gender. Turns out that even in the womb, a woman’s voice is liked and trusted. We are not only wired for speech but for female speech. The research showed that female voices win hands down. There are also fascinating insights into the personas chosen, all very different. 

The chapter on AI, machine learning, deep learning, backpropagation, supervised and unsupervised learning is told well, not too technical. The technology behind speech recognition, language understanding and speech generation is also readable. Good also to see the issue of information retrieval from both structured and unstructured data dealt with - search, knowledge graphs, the Stanford Question Answering Dataset. 

He then moves on to the next level with a chapter on ‘conversation’ describing progress through competitions to win the Alexa Prize, Loebner Prize and Winograd Scheme Challenge, These show how difficult it is to sustain conversation in chatbots, with the need for human scripting as well as an ensemble of programming and AI techniques. Above all you learn that the data gathering makes these systems better and better. As Vlahos says, “Voice AIs blur boundaries” of intimacy, privacy, mind and machine, fact and fiction, life and death.

The implications when voice becomes a dominant force may be the weakening of ad revenue as a business model. How do you get your voice heard? Mobile is accelerating voice as are home devices and the demand for voice search and smart assistants. Voice is here to stay and although people think that AI has a heart of stone, chatbots and voice bring humanity to technology. It is an illusory humanity, of course, but it can represent and reflect us, making technology at least more humane, certainly more usable.

Not much has been written on ‘voice’ despite its dramatic rise in consumer technology so for anyone who is involved in AI, chatbots, IOT and wants a feel for this particular strand of technology, this book mines the voice vein rather nicely.

PS

It is a pity that this is not being adopted more widely in online learning, beyond language learning. We have ‘voice recognition’ working in WildFire, an AI content generation tool that creates online learning in minutes not months.

Hearables are hear to stay in learning - podcasts, learning, language learning, tutoring, spaced-practice and cheating in exams!

Hearables are wearable devices that use your sense of hearing, smart headphones if you wish, that are becoming popular on the rise of voice as a significant form of interaction. With voice rising dramatically as a means of search, Amazon Echo/Google Home into millions of homes, realtime translation and earbuds for music and voice on mobiles, we are increasingly using hearing as the sense of choice for communications. 

Apples’s removal of the audio jack and launch of their EarPods was a landmark in the shift towards wireless hearables but other devices are also available or in development. Some rely on your smartphone, others, such as the Vinci, are independent, with local computing power and storage. You can even get them designed for your own ears through 3D printing.

Voice in learning
The advantages of audio in learning is in line with the simple fact that voice is primary in language, as we are all auditory grammatical geniuses, able to listen and speak, by the age of three, without instruction,  whereas reading and writing take years of instruction and practise. It is a more natural form of communication, more human. It also leaves your imagination free to create or generate your own thoughts and interpretations. This pared back input, arguably, allows deeper processing and learning as it requires attention, focus and effortful learning. Most of our communication is through dialogue and hearing, not print and most teaching takes place through hearing and dialogue.
So, there are several ways hearables could be used in learning:

1. Radio

Radio predates TV and modern media for learning. It remains a popular form of communications, as it is undemanding, leaves you hands free (while making breakfast, driving the car and so on). It also has a long history in learning, in Australia and other regions where distances are huge and resources low. The straight delivery of radio via hearables is the baseline.

2.Podcasts

Podcasts have also become a popular medium, especially for learning. They appeal to the learner who wants to focus on hearing experts, often interviewing other experts, on specific topics. As they are downloadable, they provide audio on demand, when you have the time to listen, often in those periods when you can focus, listen and learn.

3. Online learning

We have been using voice to deliver online learning in WildFire, with zero typing, as all navigation and input is by voice. It is a facsinating experience and feels more like normalised teaching and learning, when compared to using a keyboard.

4. Language learning

Language learning is an obvious application, where listening and comprehension can be delivered to your personal needs, with appropriate levels of feedback, even voice rand pronunciation recognition.

5. Translation

Translation in real time is already available through Google's Pixel Buds. The advantages, in terms of convenience, but also language learning, has huge potential. It must surely be worth exploring the advantages for novice language learners of hearing with translation and playback in the real world, where immersion and interactions with native speakers matters.
6. Tutoring
Have you ever had to call someone for help on how to fix something or get technical help on your computer? As a form of quick tutoring, voice is useful as you are hands free to try things, while you have access to experts anywhere on the planet.

7. Health

Hearables that deliver notifications on heart rate, oxygen saturation, calories burned, distance, speed and duration are available and as they can be used during exercise, may prove popular. This health learning loop also has potential to modify behavior, from diabetes to obesity.

8. Lifelong learning

As one gets older, reading, typing and other forms of interaction become more difficult. Hearables provide an easier and more convenient form of interaction, especially when combined with ‘reminders’ for those with memory problems.

9. Spaced practice

Audio could be used as a spaced-practice tool, pushed to you at intervals personalised to your needs and your own forgetting curve, namely more at the start then levelling out over time.

10. Exam cheating

Lastly, although undesirable, there have already been many instances reported of exam cheating using hearables. Ebay is awash with cheating devices such a micro-earpieces, Bluetooth pens and so on. In some ways this shows how powerful such devices can be for the timely delivery of learning!

Conclusion

Hearables are becoming part of the consumer technology landscape and in terms of learning, will have an impact. Different devices have different affordances but there is no doubt that hearing is a sense of choice for many people. Hearables, therefore, are hear to stay.

Is teaching becoming obsolete with GPT4o? Do we now have a UNIVERSAL TEACHER?

I have written and talked about the idea of a UNIVERSAL TEACHER for a long time, notably in my new book, where I go into detail about the learning theory behind 'dialogue' in learning and the key role of chatbots in teaching and learning. This is what AI promised to deliver. A free teacher who speaks, listens, remembers, tutors, using all media types, can read handwriting, provide personalised feedback, on any subject, anytime, anywhere, in any language.

What I never imagined was that it would come so fast. Yet OpenAI has delivered on what I thought was this utopian idea. In their demo they showed this in action. A frictionless, fast and sophisticated tutor. 

Open AI has become the Apple of AI. They understand, like Steve Jobs, that the user experience is all. This is especially true in teaching and training. Of all the applications, teaching and learning is the one that has most to gain from GPT4o. They may have out-Appled Apple, as Siri, Google assistant and Alexa are nowhere near as good as this. At this rate, teaching is rapidly becoming obsolete.

Realtime teacher dialogue

You can chat with it in realtime as it has realtime speech and, in the live demo, understands your voice, your emotions as expressed through your voice, even your facial expressions. You can have dialogue just as you would with a real teacher, you can interrupt it and it responds fast, as fast as a real teacher. It can generate a teacher’s voice in many styles – funny, friendly, serious, academic… whatever. The teacher’s voice is extraordinarily realistic.

Emotions

Real maths problem taughtThere was lots of pre-launch chat, stimulated by Altman, about the movie 'Her'. We now see why. The system is very 'chatty'. Indeed the fact that you can define the character by asking it to be someone, is astounding. This is a shift in branding away from Google's serious sounding assistant towards a real, emotional definition of a chatbot, so that it can play any defined role. The possibilities from different type of teachers, tutors, trainers and instructors to role playing with patients, customers and employees, even therapists, are endless.They showed a maths problem, with the learner doing it on paper, the handwritten problem, then shown to his smartphone. 

He shows her a linear equation:  3x+1=4. 

The tutor suggests he get all numbers on one side, giving a hint.

He subtracts 1 from both sides to give 3x=3. 

How does this look? He asks.

She congratulates him.

He asks for a hint for the next step. 

What undoes multiplication? She asks. 

He suggests subtraction but she says, think of the opposite of multiplication. 

He says division? 

Go ahead and divide both sides by 3 she instructs.

He does this and the solution is x=1

Well done you’ve solved it, she replies.

He then asks for real world applications and she gives him several. The tutor is endlessly patient, friendly, gives relevant feedback and can read his written steps in moving towards a solution.

In another teaching problem, by Salman Khan, you ask it to be a tutor and it talks you through a maths problem around the sides and angles in a right-angled triangle. There’s great back and forth dialogue between the student and AI, with hyper-personalised feedback and reinforcement. It does everything at the pace of the learner, behaves just like a patient tutor and corrects any errors the learner makes. All by simple showing the problem and the learner’s efforts to his smartphone. Although one has to be careful with staged examples, as it isn't doing much 'hard reasoning' here. That may be there already, it will certainly come. There is also the issue of having to show it an image, the next step is surely to draw and write on the screen as an option.

I wrote about Khan almost a decade ago, saying he was an important figure, way beyond Robinson, Mitra and many others. OpenAI have been wise in teaming up with Khan on education.

Some great features in this teaching video. For example, when the tutor is talking, if you start speaking, it stops and waits for your response. Focus on the voice of the teacher - it's very neat. The intonation is also interesting, teacher-tone. and it can be adjusted to suit any individual or audience. Its endless patience removes the frustration that every teacher and parent feels when teaching, as it defuses the stress.

One thought I did have, which is almost existential - if it can teach and do all of this maths, why would we teach it. Roger Schank used to go on about this a lot - why teach skills that can be automated, especially algebra and geometry? In any case the focus is often on maths as that is an area of catastrophic failure for many kids and adults. Maybe AI will solve the problem by solving the maths itself, not teaching millions to do what can be done in a millisecond by voice and AI.

Multimodal teaching

As a teacher it can read text, recognise images and video, just like a real teacher. In another example, the voice app on your desktop helps the learner solve a code problem, understands the written code on the screen, also the voice of the learner. She explains what the ‘foo’ function is, step by step. More than this you can then ask it to see the data visualisation that the code produces. Ask it questions about the graph and itinterprets the graph for you. So it can teach you maths, code and data analysis.

Translation

It also does real time translation, so you can teach in one language, give feedback in another, great for people learning in a second language. The possibilities in language learning are also mind blowing.

Accessibilty

The accessibility featured of GenAI often overlooked. I bang on abut this all the time and has just been boosted by GPT4o. Text2speech, speech2speech, now highly personalised dialogue. 'Bemyeyes' with GPT4o is amazing. The fact that it is free is also a huge boon for access by the poor and all who are excluded due to cost.

Administration

There was already an administrative function at enterprise level for GPTs, already used by some global companies, such as Moderna. This will be extended. It is at this organisational level that they will make money.

Conclusion

GPT4o is better than GPT4 and hammers other models. It is also faster and smarter across text, vision and audio, truly multimodal. What have they done and how? Behind the scenes the optimisation needed to deliver low-latency audio to audio in real time is massively impressive. This is not trivial as dialoghue overlaps, interrupts and is difficult to map This is a huge leap on ease of use in dialogue and intelligence with low latency, necessary for the smooth dialogue needed in tutoring. It reasons across text, voice and vision, making the teaching experience seem like a real human teacher. This could revolutionise teaching, accelerate learning, even accelerate home-schooling, maybe the end of the personal tutoring business. I feel that this is a game changer for parents as well as teachers. As a first step this is astonishing, as it is a globally scalable solution to a problem that has plagued education, where teacher shortages and costs are a problem. This is a great leveller.

The fact that the branding is GPT4o is tantalising, as if they have something else up their sleeves - GPT5? But what they have done is redefined AI as something that becomes more human using dialogue. This shift in our relationship with computers is fundamental.

Of course, this still needs testing across a range of examples but this is an astounding start. There is no stopping of progress here, the UNIVERSAL TEACHER will happen, and soon. The future is now.

PS

Noted they were using iPhones and a deal was stuck yesterday with Apple - something very big is brewing there.

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.

Are 'chatbots' a gamechanger in learning? 10 reasons and some warnings!

This was the debate motion at the LPI conference in London. I was FOR the motion (Henry Stewart was AGAINST) and let me explain why....

1. AI is a gamechanger

AI will change the very nature of work. It may even change what it is to be human. This is a technological revolution as big as the internet and will therefore change what we learn, why we learn and how we learn. The Top Seven companies by market cap all have AI as a core strategy; Apple, Alphabet, Microsoft, Amazon, Tencent, Facebook and Alibaba. AI is a strategic concern for every sector and every business, even learning. Nevertheless we must be careful not to hype their functionality. They are not capable of fully understanding every question you throw at them, neither do they have the general human capabilities of a teacher. They are, essentially, good within narrow parameters. We must manage expectations here.

2. Evidence from consumers

Several radical shifts in consumer online behavior move us towards chatbots. First the entry of voice activated bots into the home and connected the the IoT (Internet of Things) – Amazon Alexa and Google Home. My Alexa is linked to my internet music service, lights in my home and I use it a a timer for Skype calls and events during the day. It is integrated into my workflow.
3. Rise of voice
The rise of ‘voice’ as a natural form of communicating with technology – Siri, Cortana and other similar services. Over 10% of all search is now by voice. We have been using computer generated voice from text files in WildFire for some time. It adds some humanity to what can often be seen as the sterility of online learning.
4. Chat has superseded social media
The switch from social media to messaging/chat apps took place in late 2014 and the gap is growing – chat is the home screen for most young people. Look over someone's shoulder and you're far more likely to see a 'chat' screen than a website. The lesson here is that chatbots allow us to play to the natural online behaviours of learners. Then again, chat with another human is a little different from chat with a chatbot, far more limited.
5. Social
We are social animals and it was no accident that chatbots first emerged in social tools such as facebook and Slack. They are a natural extension of existing social learning, allowing us to place them in the workflow. Chatbots, like Otto, are designed to lie within these workflow tools, moving learning from the LMS to a more demand-driven model.

6. Pedagogy in chatbots

Most teaching is through dialogue. The Socratic method may have been undermined by blackboards and their successors through to PowerPoint, but voice and dialogue are making a comeback. Speaking and listening through dialogue is our most natural interface. We’ve evolved these capabilities over 2 million years, it’s natural and we’re grammatical geniuses aged 3, without having to be taught to speak and listen. Within dialogue lies lots of pedagogically strong learning techniques; retrieval, elaboration, questions, answers, follow ups, examples and so on. It just feels more natural. Once again, however, we must be careful in thinking of chatbots as people. They are not conscious and not capable of full-flow, open dialogue.

7. Evidence in learning

An exit poll taken by Donald Taylor, from Learning and Technologies conference this year, showed Personalised learning at No 1 and AI and No 3. The interest is clearly strong and there’s lots of real projects being delivered to real clients from WildFire, Learning Pool and so on. However, be careful about vendors telling you their chatbot is true AI. Many are not. It is fiendishly difficult to do this well, so most are very structured, branching bots with limited functionality.

8. Chatbots across the learning journey

There are now real chatbot applications at points across the entire learning journey. I showed actual chatbot applications in learning in the following areas:

   Recruitment bots   
   Onboarding bots

   Learner engagement bots

   Learner support bots

   Invisible LMS bots

   Mentor bots
   Reflective bots

   Practice bots

   Assessment bots

   Wellbeing bots
The problem we have is that most bots are actually just FAQ bots. They are pixies for search. In the learning game they have much more potential. My own view is that we'll see a range of bot types emerge that will match the needs of learners and organisations. We must think more expansively around bots if they are to play a significant role in learning.

9. They’re learners

An important feature of modern chatbots, compared to ELIZA from the 1960s, is the fact that they now learn. This matters as the more you train and use them, the better they get. We used to have just human teachers and learners, we now have technology that is both a teacher and learner. This means one can take advantage of bot services from some of the large tech companies. But be careful - it's not cheap and they tend t swap out functionality with little sensitivity around your delivery.

10. It’s started

Technology is always ahead of the sociology, which is always ahead of learning and development. Yet, we see in these many projects, even with relatively primitive technology and emerging trend – the use of technology delivered chatbot learning. In time, this will happen. I've been involved in several projects now across a range of chatbot types.

Objections

Nigel Paine chaired the debate with his usual panache and teased questions out of the audience and the real debate ensued. The questions were rather good.

Q Has AI has passed the Turing test?

First, there are many versions of the Turing test but the evidence from the many chatbots on social media all the way to Google Duplex, shows that it has been passed but only in limited areas. Not for long, sustained and very detailed dialogue, but certainly within limited domains. Google Duplex showed that we’re getting there on sustained dialogue and the next generation of Amazon’s Alexa and Google Home will have memory, context and personalisation in their chatbot software. It will come in time.

Q AI can never match the human brain

This is true but not always the point. We didn’t learn to fly by copying the wings of a bird – we invented new technology – the airplane. We didn’t go faster by looking at the legs of a cheetah, we invented the wheel. The human brain is actually a rather fragile entity. It takes 20 years and more of training to make it even remotely useful in the workplace, it is inattentive, easily overloaded, has fallible memory, forgets most of what its tries to learn, has tons of biases (we're all racist and sexist), sleeps 8 hours a day, we can’t download, can’t network and we die. But it is true that it is rather good at general things. This is why chatbots are best targeted at specific uses and domains, such as the species of chatbot I listed earlier.

Q Chatbots v people

Michelle Parry-Slater made a good point about chatbots not replacing people but working alongside people. This is important. Chatbots may replace some functions and roles but few suppose that all people will be eliminated by chatbots. We have to see them as being part of the learning landscape.

Q Chatbots need to capture pedagogy

Good question from Martin Couzins. Chatbots have to embody good pedagogy and already do. Whether it’s models of engagement, support, learning objectives, invisible LMS, practice, assessment or well being, the whole point is to use both the interface and back-end functionality (important area for pedagogic capture) to deliver powerful learning based on evidence-based theory, such as retrieval, effortful learning, spaced-practice and so on. This will improve rather than diminish or ignore pedagogy. In all of the examples I showed, pedagogy was first and foremost.

Q Will L and D skills have to change

Indeed. I have been training Interactive Designers on chatbot and AI skills as this is already in demand. The days of simply producing media assets and multiple choice questions is coming to a close – thankfully.

Conclusion

Oh and we won the debate by some margin, with a significant number changing their minds from sceptics to believers along the way! That doesn't really matter, as it was a self-selecting audience - they came, I'd imagine, as they were curious and had some affinity with the idea that chatbots have a role. My view is these debates are good at conferences - by starting with a polarised position, the audience can move and shift around in the middle. The audience in this session were excellent, with great questions, as you've seen above. Note to conference organisers - we need more of this - it energises debate and audience participation.