Tracy Allison Altman

By

Digital Health Network
1. #rapidisthenewblack The need for speed is paramount, so it’s crucial that we test ideas and synthesize evidence quickly without losing necessary rigor. Examples of people working hard to get it right: The Digital Health Breakthrough Network is a very cool idea, supported by an A-list team. They (@AskDHBN) seek New York City-based startups who...
Read More
1. Management research: Alchemy → Chemistry? McKinsey’s Michael Birshan and Thomas Meakin set out to “take a data-driven look” at the strategic moves of newly appointed CEOs, and how those moves influenced company returns. The accompanying podcast (with transcript), CEO transitions: The science of success, says “A lot of the existing literature is quite qualitative,...
Read More
1. Behavioral economics → Healthcare innovation. Jaan Sidorov (@DisMgtCareBlog) writes on the @Health_Affairs blog about roadblocks to healthcare innovation. Behavioral economics can help us truly understand resistance to change, including unconscious bias, so valuable improvements will gain more traction. Sidoro offers concise explanations of hyperbolic discounting, experience weighting, social utility, predictive value, and other relevant...
Read More
1. Systematic review: Does business coaching make a difference? In PLOSOne, Grover and Furnham present findings of their systematic review of coaching impacts within organizations. They found glimmers of hope for positive results from coaching, but also spotted numerous holes in research designs and data quality. Over the years, outcome measures have included job satisfaction,...
Read More
1. What new analytics are fueling baseball decisions? [I spoke at Nerd Nite SF about recent developments in baseball analytics. -Tracy Allison Altman, Ed.] Highlights from my talk: – Data science and baseball analytics are following similar trajectories. There’s more and more data, but people struggle to find predictive value. Oftentimes, executives are less familiar...
Read More
monitor showing code
1. Confusing correlation with causation is not the Cardinal Sin of data science, say Gregory Piatetsky (@kdnuggets) and Anmol Rajpurohit (@hey_anmol): It’s overfitting. Oftentimes, researchers “test numerous hypotheses without proper statistical control, until they happen to find something interesting and report it. Not surprisingly, next time the effect, which was (at least partly) due to...
Read More
People are recognizing the critical need for meta-research, or the ‘science of science’. One focus area is understanding whether research produces desired outcomes, and identifying how to ensure that truly happens going forward. Research impact assessment (RIA) is particularly important when holding organizations accountable for their management of public and donor funding. An RIA community...
Read More
1. Academics use crazy tricks for clickbait. Turn to @TheWinnower for an insightful analysis of academic article titles, and how their authors sometimes mimic techniques used for clickbait. Positively framed titles (those stating a specific finding) fare better than vague ones: For example, ‘smoking causes lung cancer’ vs. ‘the relationship between smoking and lung cancer’....
Read More
1. Know someone who effectively promotes evidence? Nominations are open for the 2016 John Maddox Prize for Standing up for Science, recognizing an individual who promotes sound science and evidence on a matter of public interest, facing difficulty or hostility in doing so. Researchers in any area of science or engineering, or those who work...
Read More
1. Spending $ on brain training isn’t so smart. It seems impossible to listen to NPR without hearing from their sponsor, Lumosity, the brain-training company. The target demo is spot on: NPR will be the first to tell you its listeners are the “nation’s best and brightest”. And bright people don’t want to slow down....
Read More
1 3 4 5 6 7

Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

Recent Articles

15 March 2023
Can AI replace your CEO?
reference to Google's Bard AI and Microsoft's Bing AI compared to conflict at Sopranos Bada Bing
28 February 2023
What’s state-of-the-art when an AI cites sources of evidence?
DALL-E image of robot head 800x450 29sep22
30 September 2022
Can AI fake reality?
finger pointing
19 August 2021
How to blame a robot for mistakes: Do your finger pointing properly.
photo of row of townhouses seen through fisheye camera lens
12 August 2020
How Human-in-the-Loop AI is Like House Hunters