Key governance structures that countries should implement to facilitate and regulate AI adoption
AI development has raised concerns about the amplification of bias, loss of privacy, social harms, disinformation, and harmful changes to the quality and availability of care and employment. In response to growing concerns, companies, governments, and potential adopters of AI technologies have described principles they believe should be followed in order to make a product safe and trustworthy. An example of this is the NHS’s “guide to good practice for digital and data-driven health technologies”. However, we need systems in place that go beyond high-level principles to make sure that AI is developed in a responsible way.
Governance
Governance is a…
How can sequence databases providing functional annotations remain sustainable as sequence data production explodes?
The amount of genomic sequencing data being produced each year is growing exponentially. Crucial to our ability to perform useful work with this data is to understand what function a piece of DNA we’ve sequenced might perform. We rely on large, curated functional annotation databases to do much of this analysis, many of which were established in the early days of genomic sequencing when much of the curation could be done manually by a small team. …
And how can we identify the next pandemic threat?
Summary
- Modelling work that began after the SARS epidemic in 2002/3 has allowed scientists to identify the way the new coronavirus infects humans
- There are specific mutations in the current virus could potentially make it more dangerous, so it's important we look out for these
- The same approach can be used to predict which animals could carry the virus
- Citizen scientists are using these techniques to design potential treatments
Over the past 20 years, several coronaviruses have crossed the species barrier into humans, causing outbreaks of severe, and often fatal, respiratory illness. Every year, new CoV sequences are discovered. But, there…
And how close are we to this today?
Before the Covid-19 pandemic, 40 million flights, carrying almost 5 billion passengers were estimated to operate globally in 2020. This number is growing year upon year, meaning that if a new infectious strain of a disease emerges, it can spread locally and internationally at a speed and scale not seen in the past.
Despite enormous technological advances over the past few centuries, infectious diseases still threaten global health. The possibility of the rapid, unexpected spread of an infectious agent across the world has become much higher, due to increasing globalisation. …
The risk/benefit equation for embracing new digital technologies has been turned on its head
This morning, Intelligent Health UK hosted a panel discussion on the UK’s response to COVID-19, in which people on the front lines of dealing with the coronavirus crisis in the UK discussed the changes they saw going on.
A major observation from the panel was the change in the risk/benefit equation for implementing new digital health technologies.
Digital health in the UK recently received a big boost in the form of a £250 million investment by the National Health System into bringing artificial intelligence into medicine, and the formation of NHSX last year, a unit dedicated to digital transformation of…
An analysis of two recently published machine learning algorithms for tracing the source of food poisoning
This is an expansion on a commentary I originally published in Nature Reviews Microbiology. To read the article, click here.
Each year, 48 million cases of foodborne illness are recorded in the United States and 1 million cases are recorded in the UK. The vast majority of these are “sporadic” cases, where a small number of people have caught an infection from contaminated food. Tracing the source of these infections is incredibly difficult. …
A run-down on my first workshop introducing computer science students to antibiotic resistance prediction with ML
This month, I ran a workshop for around 25 computer science students in Cluj-Napoca, Romania. The workshop was part of a two-day symposium on ML in biology, organised by the Romanian Society of Bioinformatics.
Machine learning is helping us discover high-risk diseases faster
Summary
- Researchers have uncovered a new strain of salmonella resistant to all but one antibiotic available in the Democratic Republic of the Congo
- This is part of an ongoing process of evolution, which may be spawning more dangerous strains over time
- This evolution can be detected by a recently-developed machine learning algorithm, allowing faster detection and containment of high-risk strains
Most salmonella infections result in symptoms associated with food poisoning. While unpleasant, these symptoms are usually not life-threatening.
But in sub-Saharan Africa, salmonella can evolve to cause bloodstream infections, becoming what are known as invasive non-typhoidal Salmonella (iNTS). Every year, iNTS…
Machine learning could solve the antibiotic resistance crisis. Will algorithms behave as well in the real world as they do in the lab?
Antimicrobial resistance is becoming a serious concern— currently antimicrobial resistant infections kill over 700,000 people per year. By 2050 its estimated 10 million people will die from of antimicrobial resistant infections.
A way to help stop the spread of antibiotic resistance
A lot of infections are treated “empirically”, meaning that if the doctor has an idea of what bacteria you’re infected with, they will prescribe a standard antibiotic to treat it. This means that if you have an infection that’s resistant to the standard antibiotic, while you’re taking your course of antibiotics, the bacteria are still living and replicating inside you. …
Recent criticism and praise of foreign aid strategies helps highlight what works and what doesn’t
Over $150 billion is put into foreign aid spending every year. Aid is especially important for governments in low-income countries, where it often exceeds 20% of their total expenditure. This has to be split between different priorities and strategies and naturally, some strategies are more effective than others.
With so much at stake in human lives and money, it’s important to look back and reflect on what worked and what didn’t. In the last month, several insiders have commented on the efforts of major health funders and their strategies. …
Nicole Wheeler
Bioinformatician + data scientist, building machine learning algorithms for the detection of emerging infectious threats to human health
