Can we explain AI with experiential? I say yes.
Our #1 fear: Withering under scrutiny.
I’ll be at VentureBeat’s Transform AI conference July 10-11 in San Francisco. Let me know if you’re attending; would be great to meet. -Tracy It’s not always easy staying on the AI bandwagon. Claims of algorithmic bias abound and (mis)applications threaten people’s trust. Not everyone wants their face recognized or their driver’s license scanned. Developers […]
Are you quantamental? Should you be?
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. […]
Evaluate your decision process separately from your outcomes.
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 […]
Weaponizing KPIs and debiasing decision algorithms.
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 […]
Machines Gone Wild! + Can Microlearning improve Data Science training?
1. Vigilance → Better algorithms “Eliminating bias… requires constant vigilance on the part of not only data scientists but up and down the corporate ranks.” In an insightful Information Week commentary, James Kobielus (@jameskobielus) considers the importance of Debiasing Our Statistical Algorithms Down to Their Roots. “Rest assured that AI, machine learning, and other statistical […]
1. Machines Gone Wild → Digital trust gap Last year I spoke with the CEO of a smallish healthcare firm. He had not embraced sophisticated analytics or machine-made decision making, with no comfort level for ‘what information he could believe’. He did, however, trust the CFO’s recommendations. Evidently, these sentiments are widely shared. — […]