Instead of setting New Year’s resolutions I’ve decided to instead make plans. Unlike resolutions, which feel like a big commitment, plans are adaptable, flexible and fluid. And also I’ll feel like less of a failure when my plans change (because, life) than I would if I break a resolution. So, here are the professional and personal plans for 2019.

Three years ago I deleted my Facebook account and have not missed a single thing that I care about. Late last year I deleted the Twitter app from my phone and tablet and as a result, stopped checking Twitter every day (I’ve been back once in the past month). I thought that I’d just probably continue to visit in the browser but now that it’s not on my phone I find that I just don’t think about it very much and, contrary to what I expected, I don’t miss it at all. Posts from this blog will keep being sent to Twitter for the time being but I may switch that off as well. Deleting an app from my phone seems like such a small thing but it’s really a thread that, when pulled, causes everything else to move. At some point, I’ll write about my reasons for moving away from social media. In the meantime, I’ll be experimenting with using this site to share the things that I find interesting, as well as more personal stuff.

My writing plans include putting aside an hour and a half every day during the week, usually from 08:30-10:00, which is just for me to write. Obviously, this will need to adapt to the requirements of teaching and admin but that’s my plan. I’m hoping to do a lot more writing both formally (i.e. academic papers) and informally (e.g. writing for The Conversation, and blogging). I currently have 11 articles under review, which I hope to get published during 2019 along with a few more ideas for papers that I have in the pipeline. These are mostly the result of clearing a backlog of papers arising from several projects that came to an end during 2017-2018. Since I don’t have any data from projects that are currently up and running my 2019 articles will most likely be more position/opinion papers that I’m using to build a foundation for my thinking around AI in healthcare and education. Once I’ve used those papers to consolidate the vocabulary and establish a few lines of inquiry, I’ll build a research agenda that should see me through the next 3-5 years.

I have two research projects that I’m busy spinning up; one on internationalisation with student exchange and another on the social implications of AI. The internationalisation project has been funded and includes a 2-week visit to Oslo, along with 5 of our undergraduate students. We’ll also be hosting 3 OsloMet colleagues and 5 of their students in Cape Town as part of the exchange programme. The implications of AI is something that’s been on my mind for the past year or so and I feel like I’m comfortable enough with the topic that I can start building a research plan around it. I’m really excited about these two projects and will share more of the details once we’ve nailed them down.

In May I’ll also be travelling to Geneva for the WCPT conference after having had two abstracts accepted. As part of that visit, I’m working with Ben Ellis, Joost van Wijchen and Guillaume Christe to plan the first In Beta Unconference, which will most likely take place in the days following the conference. If you’re interested in physiotherapy education then watch this space for an announcement in the next couple of weeks. This is part of our bigger plans to develop the In Beta community, which I wrote about during a reflection on 2018. This will most likely be my last time attending WCPT and in future, I’ll be looking at AMEE as my biennial international conference. I’ll also try to attend our local SAAHE conference, although that may not be possible given the significant expense of travelling to Geneva.

I’m going to try and expand the SAAHE podcast conversations that we started last year to include conversations with leaders in health professions education, in addition to the PhD graduates who I’ve been talking to so far. The idea is to talk about the development pathways of academics who have done a lot to drive growth in health professions education. I recorded three conversations near the end of last year and have another few planned for the next couple of months. However, like the In Beta podcast, the biggest challenge is getting the audio edited.

A few years ago I did what I called my 365 project, which was simply taking a photo a day for a year. I’ve re-started the project and have been reminded of just how many things I see every day that are quite beautiful. This is something that I’m really looking forward to, as the collection of a year’s worth of daily photos is both inspiring and wonderful to look back on.

Day 9 of the 365 project: Gaura flowers in the garden.

I’m going to try and get back into playing Go, which I did for a few years and then dropped. I really enjoyed it and can’t remember why I stopped. Last year my wife bought me a Go board (I still need the stones) so hopefully, that’ll be a big enough push to get me started again. Maybe I’ll teach the girls to play.

It’s a bit cliched but I’d like to get more exercise in 2019, especially on the moutain bike. It takes me 10 minutes to cycle to the Tokai mountain bike trails and it’s ridiculous that I don’t go more often.

Mountain biking in Tokai.

I try to read for about 3-4 hours a day and in 2018 I read 30 books (including Neal Stephensons Baroque Cycle trilogy, and Stephen Pinker’s Better Angels of our Nature, which are huge monsters) and 5.1 million words in Pocket. My daily reading time includes the minimum of 2 hours I spend commuting during the week, during which I mostly listen to articles I’ve saved in Pocket. I’ve now done a bit of re-shuffling of my daily schedule in an attempt to carve out a little bit more time for reading academic papers, which I’ve realised has been neglected since finishing my PhD.

During the last few weeks of the holidays we spent quite a bit of time spring cleaning the house and doing a bit of work in the garden. Even though we moved in 3 years ago there were still boxes and cupboards that were essentially the same as when we first arrived and dumped stuff into them to get it all off the floor. We did a huge cleanup in the garage, hung some pictures on the walls, donated a ton of stuff to charity, and finally moved an armchair into the study, which I’ve been wanting to do for at least 2 years. The change in my headspace has been amazing and so I’m planning to do more work around the house and garden in 2019. Related to this is the idea that we’d like to go away more for short breaks rather than having a single holiday at the end of the year. We spent 3 days in Greyton earlier this month and it was wonderful to get away somewhere quiet. So we’ll try to build in a few shorter breaks during 2019.

Standing in the Gobos River just outside of Greyton.

I’m going to continue my “No working in the evenings and on weekends” policy, which seems to have gone well in 2018. It means that I need to be really intentional during the 8-9 hours when I’m at work but then when I’m at home I’m mentally not at work, which has been great for my mental health. Speaking of which I’m going to reboot my attempts at daily meditation, spurred in part by the fact that I now have free access to the Waking Up app by Sam Harris as a result of being a paid subscriber to his podcast.

If I get through 2019 having achieved some of what I’ve described here, I think I’ll be pretty happy. If you read this far, thanks and all the best to you for the year ahead.

Questions for Artificial Intelligence in Health Care

Artificial intelligence (AI) is gaining high visibility in the realm of health care innovation. Broadly defined, AI is a field of computer science that aims to mimic human intelligence with computer systems. This mimicry is accomplished through iterative, complex pattern matching, generally at a speed and scale that exceed human capability. Proponents suggest, often enthusiastically, that AI will revolutionize health care for patients and populations. However, key questions must be answered to translate its promise into action.

Maddox, TM, Rumsfeld, JS, Payne, PR. (2018). Questions for Artificial Intelligence in Health Care. JAMA. Published online December 10, 2018. doi:10.1001/jama.2018.1893.

The questions and follow-up responses presented in the article are useful, highlighting the nuance that is often ignored in mainstream pieces that tend to focus on the extreme potential of the technology (i.e. what this might one day be like) rather than the more subtle implications that we need to consider today. The following text is verbatim from the article:

  1. What are the right tasks for AI in healthcare? AI is best used when the primary task is identifying clinically useful patterns in large, high-dimensional data sets. AI is most likely to succeed when used with high-quality data sources on which to “learn” and classify data in relation to outcomes. However, most clinical data, whether from electronic health records (EHRs) or medical billing claims, remain ill-defined and largely insufficient for effective exploitation by AI techniques.
  2. What are the right data for AI? AI is most likely to succeed when used with high-quality data sources on which to “learn” and classify data in relation to outcomes. However, most clinical data, whether from electronic health records (EHRs) or medical billing claims, remain ill-defined and largely insufficient for effective exploitation by AI techniques.
  3. What is the right evidence standard for AI? Innovations in medications and medical devices are required to undergo extensive evaluation, often including randomized clinical trials and postmarketing surveillance, to validate clinical effectiveness and safety. If AI is to directly influence and improve clinical care delivery, then an analogous evidence standard is needed to demonstrate improved outcomes and a lack of unintended consequences.
  4. What are the right approaches for integrating AI into clinical care? Even after the correct tasks, data, and evidence for AI are addressed, realization of its potential will not occur without effective integration into clinical care. To do so requires that clinicians develop a facility with interpreting and integrating AI-supported insights in their clinical care.

Are you ready? Here is all the data Facebook and Google have on you

Google offers an option to download all of the data it stores about you. I’ve requested to download it and the file is 5.5GB big, which is roughly 3m Word documents. This link includes your bookmarks, emails, contacts, your Google Drive files, all of the above information, your YouTube videos, the photos you’ve taken on your phone, the businesses you’ve bought from, the products you’ve bought through Google.

They also have data from your calendar, your Google hangout sessions, your location history, the music you listen to, the Google books you’ve purchased, the Google groups you’re in, the websites you’ve created, the phones you’ve owned, the pages you’ve shared, how many steps you walk in a day…

Curran, D. (2018). Are you ready? Here is all the data Facebook and Google have on you.

I’ve been thinking about all the reasons that support my decision to move as much of my digital life as possible into platforms and services that give me more control over how my personal data is used. Posts like this are really just reminders for me to remember what to include, and why I’m doing this. It’s not easy to move away from Google, Facebook, Amazon, Apple and Twitter but it may just be worth it.

Reflections on the In Beta podcast and community

It’s been about a year and a half since Ben and I started the In Beta community (see my first post in July 2017) and I wanted to reflect on what we’ve achieved in the past 18 months or so. Here are the major aspects of the project with some statistics and my thoughts on the process.

Website: We’re hosting our website on a server provided by the University of the Western Cape and use open source software (WordPress) to build the site, which means that the project costs Ben and I nothing except our time and energy. A few months ago I made a few big changes to the site, which hadn’t been updated since it launched, including a new theme and layout, new per-episode images, and an embedded media player for each episode. This is also going to be more important as the site becomes more central to our plans and needs to do more than simply distribute the audio for the podcasts.

We’ve had a fair amount of traffic since we launched the site in October 2017; far more than I expected. The numbers are obviously quite low relative to more popular sites, but consider that this is a project about physiotherapy education.

Most of our visitors came from the UK (where Ben lives) and the Netherlands (where Joost lives). I’m not sure if that’s a coincidence or if the two of them are just uncommonly popular. Incidentally, Joost has been a major supporter and promoter of the project through his connections with ENPHE and we hope that this collaboration continues to grow.

Podcasts: We’ve released 8 episodes including our first one in October 2017, so we publish about one episode every 1.5 months. We have another 3 episodes recorded but which we haven’t finished editing yet. The audio editing is, by far, the most time-consuming part of the process. We’re hoping to limit the hassle of this component by improving the quality of the initial recording, through 1) getting better at moderating the conversations and so having less to cut, and 2) making more of an effort to record better audio in the first place. Here are the 8 episodes we’ve published so far, along with the number of times each has been downloaded. These statistics exclude the first 50 or so downloads of the first episode, which was hosted on Soundcloud before we moved to our own distribution platform.

  1. Inquiry-based learning (3 October 2017) – 182
  2. Internationalisation of the curriculum (9 October 2017) – 191
  3. Clinical practice assessment forms (10 November 2017) – 158
  4. Guided choice-based learning (9 February 2018) – 82
  5. A critical pedagogy for online learning (28 February 2018) – 42
  6. New paradigms for physio education (9 May 2018) – 94
  7. Cost and value in health professions education (4 June 2018) –70
  8. Classroom-based assessment (6 September 2018) – 46

Here are the top 10 countries by number of downloads:

Projects: One of our original ideas was to use the website as a way to share examples of classroom exercises, assignments, and teaching practices that others would be able to use as a resource. The plan was to describe in a fair amount of detail the process for setting up a learning task that others could simply copy, maybe with a few minor tweaks. The project pages would include the specific learning outcomes that the lecturer hopes to achieve, comprehensive descriptions of the learning activities, links to freely available resources, and examples of student work. This aspect of In Beta hasn’t taken off as much as we would’ve liked but the potential is still there and will hopefully continue growing over time.

Google Docs: We started with Google Docs as a way to plan for our podcast recordings, using a templated outline that we’d invite guests to complete. The idea is that guests on the podcast will use the template to establish the context for the conversation, including the background, the problem they’re trying to address, and a reading list for interested participants. We then take some of that information and incorporate it into the show notes for the episode and leave the Google Doc online for further reading if anyone is interested. The process (and template) has remained more or less the same since we initially described it but I’m uncertain about whether or not we should include it going forward. It seems like a lot of PT to ask guests to complete and, without statistics for Docs, we can’t be sure if anyone is going there. On the other hand, it really does seem to be good preparation for us to have a deep dive into the topic.

Membership: We had about 100 people join the Google+ community but saw little engagement on the site. I think that this is understandable considering that most people have more than enough going on in their personal and professional lives to add yet another online destination to their lists. Most people are already on several social media platforms and it’s not reasonable to expect them to add Google+ just for this project. So we weren’t too upset to see that Google is planning to sunset the consumer version of Google+, so in some ways it’s a bit of a relief not to have to worry about managing the community in different places. We’re in the process of asking people to migrate to the project website and sign up for email notifications of announcements.

Conference collaborations: Ben and I worked with Joost to run two In Beta workshops at the IPSM (Portugal) and ENPHE conferences (Paris) in 2018. We based both sessions on the Unconference format and used them as experiments to think differently about how conference workshops could be useful for participants in the room, as well as those who were “outside” of it. While neither of the workshops went exactly how we planned, I think the fact that both of these sessions actually happened, in large part due to the work that Joost and Ben put in, was a success in itself. We’ve recorded our thoughts on this process and will publish that as an episode early in 2019. It’d be nice to have more of these sessions where we try to do something “in the world”.

Plans for 2019: Our rough ideas for the next 12 months include the following:

  • More frequent podcast episodes, which should be possible if we can reduce the amount of time it takes to edit each episode. It’d also be nice to get assistance with the audio editing, so if you’re interested in being involved and have an interest in that kind of thing, let us know.
  • Work on more collaborative projects with colleagues who are interested in alternative approaches to physiotherapy education. For example, it might be interesting to publish an edited “book” of short stories related to physiotherapy education. It could be written by students, educators and clinicians, and might cover a broad range of topics that explore physiotherapy education from a variety of perspectives.
  • Grow the community so that In Beta is more than a podcast. We started the project because we wanted to share interesting conversations in physiotherapy education and we think that there’s enormous scope for this idea to be developed. But we also know that we’re never going to have all the good ideas ourselves and so we need to involve more of the people doing the interesting work in classrooms and clinical spaces around the world.
  • Host a workshop for In Beta community members, possibly at a time when enough of us are gathered together in the same place. Maybe in Europe somewhere. Probably in May. Something like a seminar or colloquium on physiotherapy education. If this sounds like something you may like to be involved with, please let us know.

It’s easy to forget what you’ve achieved when you’re caught up in the process. I think that both Ben and I would probably like to have done a bit more on the project over the past 18 months but if I look at where we started (a conversation over coffee at a conference in 2016) then I’m pretty happy with what we’ve accomplished. And I’m excited for 2019.

Delete All Your Apps

A good question to ask yourself when evaluating your apps is “why does this app exist?” If it exists because it costs money to buy, or because it’s the free app extension of a service that costs money, then it is more likely to be able to sustain itself without harvesting and selling your data. If it’s a free app that exists for the sole purpose of amassing a large amount of users, then chances are it has been monetized by selling data to advertisers.

Koebler, J. (2018). Delete all your apps.

This is a useful heuristic for making quick decisions about whether or not you should have that app installed on your phone. Another good rule of thumb: “If you’re not paying for the product then you are the product.” Your personal data is worth a lot to companies who are either going to use it to refine their own AI-based platforms (e.g. Google, Facebook, Twitter, etc.) or who will sell your (supposedly anonymised) data to those companies. This is how things work now…you give them your data (connections, preferences, brand loyalty, relationships, etc.) and they give you a service “for free”. But as we’re seeing more and more, it really isn’t free. This is especially concerning when you realise how often your device and apps are “phoning home” with reports about you and your usage patterns, sometimes as frequently as every 2 seconds.

On a related note, if you’re interested in a potential technical solution to this problem you may want to check out Solid (social linked data) by Tim Berners-Lee, which will allow you to maintain control of your personal information but still share it with 3rd parties under conditions that you specify.

Split learning for health: Distributed deep learning without sharing raw patient data

Can health entities collaboratively train deep learning models without sharing sensitive raw data? This paper proposes several configurations of a distributed deep learning method called SplitNN to facilitate such collaborations. SplitNN does not share raw data or model details with collaborating institutions. The proposed configurations of splitNN cater to practical settings of i) entities holding different modalities of patient data, ii) centralized and local health entities collaborating on multiple task

Source: [1812.00564] Split learning for health: Distributed deep learning without sharing raw patient data

The paper describes how algorithm design (including training) can be shared across different organisations without each having access to each other’s resources.

This has important implications for the development of AI-based health applications, in that hospitals and other service providers need not share raw patient data with companies like Google/DeepMind. Health organisations could do the basic algorithm design in-house with the smaller, local data sets and then send the algorithm to organisations that have the massive data sets necessary for refining the algorithm, all without exposing the initial data and protecting patient privacy.

First compute no harm

Is it acceptable for algorithms today, or an AGI in a decade’s time, to suggest withdrawal of aggressive care and so hasten death? Or alternatively, should it recommend persistence with futile care? The notion of “doing no harm” is stretched further when an AI must choose between patient and societal benefit. We thus need to develop broad principles to govern the design, creation, and use of AI in healthcare. These principles should encompass the three domains of technology, its users, and the way in which both interact in the (socio-technical) health system.

Source: Enrico Coiera et al. (2017). First compute no harm. BMJ Opinion.

The article goes on to list some of the guiding principles for the development of AI in healthcare, including the following:

  • AI must be designed and built to meet safety standards that ensure it is fit for purpose and operates as intended.
  • AI must be designed for the needs of those who will work with it, and fit their workflows.
  • Humans must have the right to challenge an AI’s decision if they believe it to be in error.
  • Humans should not direct AIs to perform beyond the bounds of their design or delegated authority.
  • Humans should recognize that their own performance is altered when working with AI.
  • If humans are responsible for an outcome, they should be obliged to remain vigilant, even after they have delegated tasks to an AI.

The principles listed above are only a very short summary. If you’re interested in the topic of ethical decision making in clinical practice, you should read the whole thing.

MIT researchers show how to detect and address AI bias without loss in accuracy

The key…is often to get more data from underrepresented groups. For example…an AI model was twice as likely to label women as low-income and men as high-income. By increasing the representation of women in the dataset by a factor of 10, the number of inaccurate results was reduced by 40 percent.

Source: MIT researchers show how to detect and address AI bias without loss in accuracy | VentureBeat

What many people don’t understand about algorithmic bias is that it’s corrected quite easily, relative to the challenge of correcting bias in human beings. If machine learning outputs are biased, we can change the algorithm, and we can change the datasets. What’s the plan for changing human bias?

My presentation for the Reimagine Education conference

Here is a summarised version of the presentation I’m giving later this morning at the Reimagine Education conference. You can download the slides here.

E.J. Chichilnisky | Restoring Sight to the Blind

Source: After on podcast with Rob Reid: Episode 39: E.J. Chichilnisky | Restoring Sight to the Blind.

This was mind-blowing.

The conversation starts with a basic overview of how the eye works, which is fascinating in itself, but then they start talking about how they’ve figured out how to insert an external (digital) process into the interface between the eye and brain, and that’s when things get crazy.

It’s not always easy to see the implications of converting physical processes into software but this is one of those conversations that really makes it simple to see. When we use software to mediate the information that the brain receives, we’re able to manipulate that information in many different ways. For example, with this system in place, you could see wavelengths of light that are invisible to the unaided eye. Imagine being able to see in the infrared or ultraviolet spectrum. But it gets even crazier.

It turns out we have cells in the interface between the brain and eye that are capable of processing different kinds of visual information (for example, reading text and evaluating movement). When both types of cell receives information meant for the other at once, we find it really hard to process both simultaneously. But, if software could divert the different kinds of information directly to the cells responsible for processing it, we could do things like read text while driving. The brain wouldn’t be confused because the information isn’t coming via the eyes at all and so the different streams are processed as two separate channels.

Like I said, mind-blowing stuff.

Additional reading