Sniffing disease markers is a fundamentally promising concept. We know that dogs have very good smell, so that is an existence proof that something interesting can be detected in the air. (In my family’s experience, human smell can also become amazingly good, at least for pregnant women!) In fact, if B.F. Skinner were still alive, I wonder if he would be training pigeons to sniff out disease?
But although air is feasible, it does seem like blood is a better choice because it is likely to have stronger signals and lower noise. Air-based sensors would be non-invasive, so perhaps that is why some groups are pursuing air.
…a team of researchers from the ..Monell Chemical Senses Center and the University of Pennsylvania [are working] on a prototype odor sensor that detects ovarian cancer in samples of blood plasma.
The team chose plasma because it is somewhat less likely than breath or urine to be corrupted by confounding factors like diet or environmental chemicals, including cleaning products or pollution. Instead of ligands, their sensors rely on snippets of single-strand DNA to do the work of latching onto odor particles.
“We are trying to make the device work the way we understand mammalian olfaction works,” … “DNA gives unique characteristics for this process.”
Judging by research at UCSD and elsewhere, I envision tests like this eventually be run as add-on modules to smartphones. Buy a module for $100 (single molecule, home use) up to $5000 (multiple molecules, ambulance use), and plug it into your phone. Above $5000, you will probably use a dedicated electronics package. But that package might be based on Android OS.
This is also another example of Big Data science. It could be done before, but it will be a lot easier now. Blood collected for other purposes from “known sick” patients could be used to create a 50,000 person training set. (The biggest problem might be getting informed consent.)
There are lots of technology-policy-related stories this weekend. The first three concern about excess market power in tech markets, and its effects. The remaining three are miscellaneous subjects at the intersection of technology, policy, and politics.
Suggestion: If a newspaper is refusing to let you read an article, you can often get it by searching for it (on Google – irony alert, see one of the stories below), and visiting from the search result.
And a humble brag: Only the last of these stories directly concerns He Who Must Not Be Named. Nor did I mention Juicero, whose idiocy I tweeted about when it first came to market.
Is It Time to Break Up Google?
In just 10 years, the world’s five largest companies by market capitalization have all changed, save for one: Microsoft. Exxon Mobil, General Electric, Citigroup and Shell Oil are out and Apple, Alphabet (the parent company of Google), Amazon and Facebook have taken their place.
They’re all tech companies, and each dominates its corner of the industry: Google has an 88 percent market share in search advertising, Facebook (and its subsidiaries Instagram, WhatsApp and Messenger) owns 77 percent of mobile social traffic and Amazon has a 74 percent share in the e-book market. In classic economic terms, all three are monopolies.
AI, machine learning, etc only appear to be objective. In reality, they reflect the world view and prejudices of their developers.
Algorithms have been empowered to make decisions and take actions for the sake of efficiency and speed…. the aura of objectivity and infallibility cultures tend to ascribe to them. . the shortcomings of algorithmic decisionmaking, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems. This report highlights the added risks and complexities inherent in the use of algorithmic … decisionmaking in public policy. The report ends with a survey of approaches for combating these problems.
Source: An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence | RAND
Why did it take so long to invent the wheelbarrow? Have we hit peak innovation? What our list reveals about imagination, optimism, and the nature of progress.
Source: The 50 Greatest Breakthroughs Since the Wheel – The Atlantic
A few years old, but still interesting. For example:
By expanding the pool of potentially literate people, the adoption of corrective lenses may have amounted to the largest onetime IQ boost in history.
Its economists used to champion big firms, but the mood has shifted
Source: Schumpeter: The University of Chicago worries about a lack of competition | The Economist
There is an emerging consensus among economists that competition in the economy has weakened significantly. That is bad news: it means that incumbent firms may not need to innovate as much, and that inequality may increase if companies can hoard profits and spend less on investment and wages.
Yes, I certainly see this in tech fields.The double consequences are scary.
Thanks to colleague Prof. Liz Lyons for suggesting this.
Same-day delivery for Amazon ” is taking an increasing toll on Yamato’s drivers because of the high volume of nighttime deliveries.”
The company had been considering partly terminating contracts with major clients who refused to accept raised shipping fees or deferring delivery days during peak periods.
Source: Overwhelmed Yamato mulls exit from Amazon’s same-day delivery service | The Japan Times
Package delivery is one of the only employment categories that is increasing as retailing moves more toward the Internet. But as this article implies, we will see more change in how retailers and deliverers manage the last step in the B-to-C supply chain. Why doesn’t Yamato raise its prices?
Why doesn’t Yamato raise its prices? Perhaps they don’t want to compete with other delivery services in late night delivery?
We yearn for frictionless technological solutions. But people talking to people is still the way that norms and standards change.
Source: Sharing Slow Ideas – The New Yorker