presenting the evidence

Category

reference to Google's Bard AI and Microsoft's Bing AI compared to conflict at Sopranos Bada Bing
Now that machines are answering questions and making decisions, it’s essential that people and AI get on the same page when citing evidence. What sources are considered acceptable? Where should citations be presented (inline, in conventional bibliographies, or…)? Should data/analysis be simply referenced, or transparently included in supporting data sets? Here we look at state-of-the-art...
Read More
woman exiting revolving door
To cut through AI complexity, focus on decisions. Never has it been more important to effectively explain complex concepts. Technology is influencing most decision processes, not always transparently so. On the bumpy road toward explainable AI (XAI), we find great communication options, from printed materials to state-of-the-art experiences. But where do you start, or know...
Read More
silver corded microphone in shallow focus photography
Jerry Seinfeld was wrong when he claimed public speaking is our #1 fear. I’m pretty sure we’re more afraid of having our decisions scrutinized. Adding to the fun, now algorithmic decisions are under pressure too. It is rather painful to have decisions second-guessed before the numbers come in, and even worse if things go pear-shaped....
Read More
Present everything better! As co-organizer of the meetups Papers We Love – Denver and Domain-Driven Design – Denver, I was delighted to co-host PitchLab for a talk on presentation skills. Jay Mays and Keefer Caid-Loos did an excellent job explaining how to connect with your audience. Participants were engaged, and appreciated PitchLab’s approachable, ask-me-anything attitude. The...
Read More
fox
1. Prior experience → More trust In Trustworthy Data Analysis, Roger Peng gives an elegant description of how he evaluates analytics presentations, and what factors influence his trust level. First, he imagines analytical work in three buckets: A (the material presented), B (work done but not presented), and C (analytical work not done). “We can...
Read More
decision bias in food-poverty policy
1. Biased analysis → Misunderstood cause-effect In Biased Ways We Look at Poverty, Adam Ozimek reviews new evidence suggesting that food deserts aren’t the problem, behavior is. His Modeled Behavior (Forbes) piece asks why the food desert theory got so much play, claiming “I would argue it reflects liberal bias when it comes to understanding...
Read More
Translators at IFLA 2010
1. Hire analytics translators → Keep data scientists happy An emerging role – what some call the Analytics Translator – is offloading burden from data scientists, while helping business executives get better value from their technology investments. A recent HBR piece explains You Don’t Have to Be a Data Scientist to Fill This Must-Have Analytics...
Read More
action->outcome in PepperSlice
Ugly Research offers a new guide, Promoting Evidence-Based Insights. Practical tips for presenting content with four essential characteristics: Top-line, evidence-based, bite-size, and reusable. Communicate quickly and powerfully by demonstrating value to decision makers. Show how A → B. So people don’t think tl;dr or MEGO (My Eyes Glaze Over), be sure to emphasize insights that...
Read More
data visualization of crime statistics using Tableau
Technology helps us discover meaningful patterns: Buying behavior, criminal activity, health effects. But when we succumb to pretty pictures and mindless measurement, shiny data fails to help answer important questions. Source: Tableau. This data visualization tool would be great for someone seeking crime stats – say, for law enforcement or house buying. But it doesn’t...
Read More
Our founder, Tracy Allison Altman, will talk about cognitive bias and behavioral economics for software design @ Papers We Love – Denver. Tversky and Kahneman’s classic “Judgment under Uncertainty: Heuristics and Biases” challenged conventional thinking about bias in decision making, inspiring new approaches to cognitive science, choice architecture, public policy, and the underlying technology. Join...
Read More
1 2 3

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?
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
coronavirus pandemic curve - johns hopkins
9 April 2020
Deciding while distancing: From data viz to the hard decisions.