- Dr. Data Show Video: How Can You Trust AI? - Oct 20, 2018.
This new web series breaks the mold for data science infotainment, captivating the planet with short webisodes that cover the very best of machine learning and predictive analytics.
Tags: AI, Eric Siegel, Machine Learning, Predictive Analytics, Predictive Analytics World, Trust
- When Do We Trust Machines? - Apr 16, 2018.
We propose a framework of "trust heatmap", show how the trust in machines depends on two key elements: their error rate and the costs of mistakes, and examine the automation frontier.
Tags: AI, Automation, Self-Driving Car, TED, Trust, Vasant Dhar
- How Not To Lie With Statistics - Jan 11, 2018.
Darrell Huff's classic How to Lie with Statistics is perhaps more relevant than ever. In this short article, I revisit this theme from some different angles.
Tags: Statistics, Trust
- Challenges in Machine Learning for Trust - May 29, 2017.
With an explosive growth in the number of transactions, detecting fraud cannot be done manually and Machine Learning-based methods are required. We examine what are the main challenges for using Machine Learning for Trust.
Tags: Machine Learning, Risk Modeling, Trust
- Big Data Desperately Needs Transparency - Mar 6, 2017.
If Big Data is to realize its potential, people need to understand what it is capable of, what information is out there and where every piece of data comes from. Without such transparency and understanding, it will be difficult to persuade people to rely on the findings.
Tags: Big Data, Interpretability, Transparency, Trust
- Cooperative Trust Among Neural Networks Drives Deeper Learning - Feb 28, 2017.
Machine learning developers need to model a growing range of multi-partner scenarios where many learning agents and data sources interact under varying degrees of trustworthiness. This IBM site helps to take next step towards continuous intelligence.
Tags: IBM, Machine Learning, Neural Networks, Trust
- Machine Learning Meets Humans – Insights from HUML 2016 - Jan 6, 2017.
Report from an important IEEE workshop on Human Use of Machine Learning, covering trust, responsibility, the value of explanation, safety of machine learning, discrimination in human vs. machine decision making, and more.
Pages: 1 2
Tags: AI, Bias, Decision Making, Humans, Machine Learning, Privacy, Safety, Transparency, Trust
- How Much Will A.I. Surprise Us? - Jun 15, 2016.
Why think about what neural networks (and AI in general) can do that we can already do, when he real question that we should be asking is this: What will A.I. be able to do that we can’t even dream of?
Tags: AI, Artificial Intelligence, Future, Trust
- Trust and Analytics in the Banking Sector - May 26, 2016.
This post explores the intricate relationship between customers, trust, and analytics in the banking sector, and offer actions that banks may need to take to assess the way they assure trust across the analytics lifecycle.
Tags: Advanced Analytics, Banking, Big Data, Finance, Trust
- The Anchors of Trust in Data Analytics - Mar 14, 2016.
An exploration of some of the critical questions and challenges emerging around trust in data and analytics. The four anchors of trust that will shape public confidence in D&A in the age of the analytical enterprise are highlighted.
Tags: Analytics, Big Data, Data Analytics, KPMG, Trust
- The Perpetual Quest for Digital Trust - Jul 22, 2015.
Digital Trust is at a deficit – concludes the 2015 Accenture Digital Consumer Survey report “Digital Trust in the IoT Era”
Tags: Accenture, Consumer Insights, Information Management, IoT, Security, Survey, Trust
- Innocentive: INSTINCT – The IARPA Trustworthiness Challenge - Mar 16, 2014.
This challenge investigates novel statistical techniques to identify neurophysiological correlates of trustworthiness. Deadline: May 5.
Tags: Challenge, Competition, IARPA, Innocentive, Neurophysiology, Trust
