How fun & games can make us better at deciding.
What we talk about when we talk about deciding: Notes from DAAG 2019
What is a fun experience really about? I’ve gained new perspective from Fun, Taste, & Games: An Aesthetics of the Idle, Unproductive, and Otherwise Playful (MIT Press). I have first-hand knowledge that the authors, John Sharp (Parsons/New School) and David Thomas, are in fact, fun: They would probably join you at Casa Bonita*. John and […]
A peek inside LMNL’s immersive experience.
Since my work is about humans+AI deciding together, I attended DAAG 2019 in beautiful downtown Denver, exploring the “intersection of decision analysis and data science to take decision-making to the next level.” The intent was for decision analysts to better understand data science and “support data-centric decision-making” while data scientists could better “guide the use […]
Our #1 fear: Withering under scrutiny.
Lucky me, I got to visit Onedome, an interactive arts and entertainment space on Market in San Francisco. Besides immersive installations, you can attend a cool 32-person F.E.A.S.T. dinner (Fine Dining, Entertainment, Art, Story & Technology). LMNL is a labyrinth offering 14 interactive rooms of digital art. I visited the LMNL exhibit: Stunning immersive visuals […]
Don’t build a data department store.
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. […]
The skill set for explaining, XAI, and why they both matter.
To paraphrase Raymond Chandler, too many projects deliver department store data: The most of everything but the best of nothing. Enterprise AI and analytics developers must avoid the mistake of underserving people by overengineering solutions. Designers and decision makers need straightforward tools to make them better, to save time and facilitate their best work. They […]
Are you quantamental? Should you be?
As data complexity grows, so does the importance of explaining. The philosophy of science can teach us about the role of explaining in high-quality, evidence-based decisions. It’s not just navel-gazing: An explanation is a statement that makes something clear, or a reason or justification given for an action or belief. It describes “a set of […]
PitchLab shows how to present complex technology.
Quantamental is an investment strategy combining quantitative and fundamental methods. Data and algorithms have “prompted many traditional fundamentals-centered discretionary funds to integrate data-driven tools in day-to-day decision-making.” MarketWatch says the quantamental merger of computing power and human expertise is investing’s next frontier. Example: Active trading based on a particular blend of conventional balance sheets and […]
Evaluate your decision process separately from your outcomes.
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 […]
What makes us trust analytics, and how to argue.
How we decide is no less important than the data we use to decide. People are recognizing this and creating innovative ways to blend what, why, and how into decision processes. 1. Apply behavioral science → Less cognitive bias McKinsey experts offer excellent insight into Behavioral science in business: Nudging, debiasing, and managing the irrational […]
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 […]