Is AI washing helpful for digital healthcare?
It has been fashionable for the past several years to invoke the term “artificial intelligence” as a ritual bath for the use of IT in healthcare. And while a level of hype can be taken with a pinch of salt in advanced economies like those of the UK, the US, and China, should we not be more alert to it when it suffuses digital healthcare in less developed countries?
Even in the UK – probably not so different to other European countries or North America – conventional data analytics seems to be of more use than much-vaunted AI systems.
This is borne out by a recent report from the Centre for Data Ethics and Innovation. To gauge how the public has been reacting to the use of digital technology during the Covid-19 pandemic, the CDEI – which is a UK government advisory body on the responsible use of AI and data technology – commissioned a survey of around 12,000 people between June and December 2020.
They also have been collecting, from March 2020, examples of where “data-driven technology, which encompasses artificial intelligence, traditional algorithmic systems, and tools and techniques from the discipline of data science” has been used to combat the Covid-19 pandemic”. They found: “artificial intelligence did not play the outsized role many thought it would in relief efforts. Instead, it has been conventional data analysis, underpinned by new data sharing agreements, that appear to have made the biggest difference to the work of health services and public authorities”.
The CDEI report reminded me of a UN “AI for Good” roundtable I sat in on earlier this year, organized by the ITU, which is a United Nations agency for telecoms and ICT [Information and Communications Technology].
There is an excellent account of the content of that roundtable on the ITU site, so I won’t try to replicate that here.
I asked the roundtable speakers what they thought the value of the term AI in healthcare is, especially in relation to the Covid-19 pandemic. Are there not dangers in over-inflating the term? Ought it not to be reined in? What is the value in describing straightforward and hugely important IT programmes in healthcare as AI? These were two of their responses.
- Ursula Jasper, Governance & Policy Lead, Fondation Botnar: “There is a certain hype and an overuse or inflation of the term. This is not unusual – it’s the same with globalization. Once the dust settles people will become more critical and see subtle and positive and negative aspects. We do need to be careful not to overuse the term, but AI and digital are here to stay, so the point is to develop a more nuanced understanding, not to get rid of it”.
- Reinhard Scholl, Deputy Director of ITU’s Telecommunication Standardization Bureau (TSB): “There are hypes. Last week it was the internet of things, and yesterday it was smart cities and today it is AI. But I still think AI is going to stick around. It is going to be the defining technology of the future. There are lots of examples of its impact. Just a few weeks ago DeepMind was able to make huge progress on the protein folding problem, to predict the dimensional structure for protein from the amino sequence. Or if you look at recommendation algorithms, which can be good or bad. AI will stay with us forever. The hope for artificial general intelligence means you have to be prepared if it does come. So, I see AI as different to other hype trends. It will be dominant”.
(The protein-folding problem is that of determining a protein’s 3D shape from its amino-acid sequence, and the significance of DeepMind’s work on the problem is discussed in this Nature article, which encapsulates it thus: “The ability to accurately predict protein structures from their amino-acid sequence would be a huge boon to life sciences and medicine. It would vastly accelerate efforts to understand the building blocks of cells and enable quicker and more advanced drug discovery”).
Nevertheless, the roundtable itself was, for me, notable for the enduring value of more “basic” IT, as in the work done in Korea to combat from the Covid-19 pandemic.
This is from the ITU article mentioned above:
“Park Soo Jun, Assistant Vice President at Korea’s Electronics and Telecommunications Research Institute, explained how digital technologies are helping Korea to fight the spread of COVID-19 with quicker screening and diagnoses.
“But it’s not the ultra-sophisticated AI that’s been the most relevant, Park pointed out. Simpler tech solutions such as smart quarantine systems, self-check health and self-protection quarantine apps and chatbots have been powerful tools in their response to the pandemic, he said. Jasper agrees that it’s ‘not about the fanciest AI’ and even simple ideas such as equipping community health workers with a mobile phone or tablet can improve clinical care.”
Now, maybe it doesn’t matter if mainstream, socially valuable IT implementations get badged as artificial intelligence.
However, what of the people who do the “conventional data analysis” referred to in the CDEI research? Is it not disrespectful of the work they do to cast it in the magical shadow of AI? Just a thought.