Just show up

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Today’s topics:

  • On the ethics of using artificial intelligence 
  • GenAI and medical information
  • The using AI = more free time fallacy
  • Leadership: Just show up

On the ethics of using artificial intelligence 

AI can accelerate research outcomes and knowledge generation. AI can review huge datasets, predict the binding properties of antibodies, propose ideal molecule structures, support with image analysis, review scientific literature, write grant proposals and scientific articles, or as recently shared by a press release on Moderna’s use of AI, calculate dosing schedules for clinical trials.

That said, the foundation of ethical scientific research remains the same:  transparency regarding the data, materials and methods used. Honest reporting of the findings and a differentiated discussion and the authors’ accountability for the findings they publish.

Authors David B. Resnik and Mohammed Hosseini, share their thoughts on “The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool” in an article published in the Journal of AI and Ethics in May 27, 2024 (Link). While the authors focus on AI in research, I believe the recommendations apply across disciplines and are worth reflecting on:

  • AI is a new tool and new guidance is needed from legislators especially beyond GenAI
  • The use of artificial intelligence and its limitations should be transparently disclosed wherever it is used
  • AI should not be listed as an authors, inventors, or copyright holders
  • Employee training should include discussions on the ethical use of AI
  • And a point I never tire of making:  when using AI or designing AI models a broad population of impacted stakeholders should be engaged to anticipate and avoid potential bias

Transparency regarding the use of AI and in communicating it in such a way that it is understandable for a non-expert is critical. While the above publication focuses on research uses of AI, and is truly worth reading, another article, the EFPIA position paper on the use of AI, with considerations focused on the pharmaceutical industry, can be found here, the themes are broadly similar.

Key take-away:  As you introduce AI ensure you have guidelines on compliant use, reporting, transparency of use, and guidance on quality control for content generated as well as employee training in place.

GenAI and medical information

Some Medical Information teams are exploring the use of GenAI to generate content to provide  Medical Information services across channels. There is a lot of interest and many abstracts on the topic have been submitted for September’s DIA Medical Information meeting in London (Sign up here).

While there are risks when using GenAI including the perpetuation of bias and stereotypes,  and the generation of hallucinations and falsifications, both of which need managing, the potential for content provision support is significant. Like everything it needs implementing in the correct way.

Some questions to ask before implementing GenAI to develop content:

  • Do you have access to high-quality content?
  • Do you have access to large volumes of content?
  • Could multiple teams/channels benefit from GenAI on the identified content?
  • Does your business case – products, volume, indications, enquiries support the implementation of Gen AI? E.g. if you sell an orphan product with highly specific customer enquiries the effort to train and maintain models is unlikely to be warranted.
  • What are the costs/cost savings over time?
  • Do you have the foundation, processes, and volume to make the investment reasonable?
  • What other teams are already working on this? Can you tag team?

Ask yourself “Why us? Why now?” 

A friend and fellow programme committee member recently said to me “think about it, when email was invented, did Medical Information teams invent email or use it? I think AI is similar, it’s a valid tool for business, but I don’t think everyone needs to develop their own model”

Key take-away: AI models need investment to implement, train and maintain, invest wisely.

Why AI will not free your time

On the afternoons when I switch off my phone to read or write without distraction, I feel incredibly calm and productive. Does the idea that technology “gobbles up your time” resonate with you?
A recent comment on a GenAI chatgroup I am on made me think about the promise of technology further. The comment was:  “I think it is thought provoking to think about what we will do with the time we have freed up? If my AI enabled works saves me two hours a day. What do I do with that time? What does the CFO and CEO expect me to do with that time?”
The answer is of course, sadly, that there will be no free time. All time saved will be reinvested. Friends of mine who are physicians are expected to see more patients now that AI assisted note taking has been implemented, no matter that this does not work well with oncology patient files. Yuval Harari wrote about the fallacy that the more we advance,  the more free time we have, in his book “Sapiens – a brief history of humankind.”  Instead, of having more time, we just experience acceleration. In the past we wrote letters, and we waited for a response. Then we wrote emails and waited. Now we write text messages and if a response/blue tick is not seen within an hour, we call to find out whether the message was read.

Or we send a text message and in parallel an email to ensure the message is received. One of my family members often checks in with me a few hours after a text message has been sent to make sure it arrived and to ask in a roundabout way what my response is. 
So instead of having more time, we spend more time managing the barrage of information we receive, speeding up to manage this, while also being more available.
It is a vicious cycle.
In most jobs we calculate productivity in hours, however,  unless you work in a fruit packing plant, or on a car assembly line, back when they were not automated, this formula does not hold true.

For all white-collar jobs that I can think of this equation has no relevance. In fact, for most jobs I think this equation has little relevance. 

The belief that hours worked = value produced needs addressing if we are to escape the cycle. 
Key take-away: Use AI and speed up at your peril but do not expect to leave earlier or to be rewarded for it.

Leadership: Just show up

Last week I had family visiting from New Zealand. I took them to a city near me with the caveat that I have to be back at my desk for meetings in the afternoon. When I got to my computer both  meetings had been cancelled. 

The cancellations were short notice, within an hour of the meeting, so I could not adapt my schedule to spend more time with my family. Instead, I was at my desk.

After these two cancellations I started taking notice. In the past two weeks, eight people have adapted meetings that have been on calendar for a long time last minute. Some individuals did not show up, some rescheduled without comment, some remembered conflicting appointments.  Two apologised, this is apparently the exception rather than the rule.

Always curious I have asked colleagues and friends for their experience. Employees tell me that no-shows, late cancellations, and last-minute rescheduling is the new normal. Consultants tell me that their clients cancel entire workshops two days and coaching sessions minutes ahead. They pay the fee without complaint and reschedule for two months later.

Flakiness is more the rule than the exception nowadays it seems. 

My hypothesis is that the more technology people have at their disposal for managing their time, the more accepted last minute text messages are for cancelling, the more people tend to commit and overcommit while not actually feeling committed. Every appointment scheduled becomes an option rather than a priority. 

Unfortunately this behaviour has a domino effect. If you reschedule the person you were going to meet has to do so too, which impacts calendars, and potentially other people down the line. 

Naturally unexpected things happen to good people and sometimes cancellations are unavoidable. When that happens try to give notice when it happens, it is easy to forget if you don’t act fast.

In situations where you know you don’t want to make an appointment with someone, aim to tell them upfront politely. If you do make an appointment, try to show up,  if you cannot show up, alert others ahead of time, reschedule if it makes sense and consider adding an apology. A little courtesy goes a long way. 

Key take-away: All you have to do is show up. In an era where good manners have become optional, even the bare minimum will put you ahead. 

If you missed the panel discussion on digital islands with Peter Shone and Wolfgang Schwerdt you can find it here: Link

I hope my posts provide you with useful insights. If  you need support with a project, or are interested in coaching, why not give me a call to see how I can help? Find out what clients say about working with me here link.

My very best wishes

Isabelle C. Widmer MD

Image credit: MJH Shikder @unsplash