Data Skeptic

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

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Website
http://dataskeptic.com
Description
Data Skeptic alternates between short mini episodes with the host explaining concepts from data science to his non-data scientist wife, and longer interviews featuring practitioners and experts on interesting topics related to data, all through the eye of scientific skepticism.
Language
🇬🇧 English
last modified
2018-10-13 11:48
last episode published
2018-08-31 15:00
Contributors
Kyle Polich author   owner  
Explicit
false
Number of Episodes
236
Rss-Feeds
Detail page
Categories
Technology Education Science & Medicine Higher Education

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Episodes

Date Thumb Title & Description Contributors
12.10.2018

louvain

Without getting into definitions, we have an intuitive sense of what a "community" is. The Louvain Method for Community Detection is one of the best known mathematical techniques designed to detect communities. This method requires typical graph data i...
5.10.2018

Cultural Cognition of Scientific Consensus

In this episode, our guest is Dan Kahan about his research into how people consume and interpret science news. In an era of fake news, motivated reasoning, and alternative facts, important questions need to be asked about how people understand new info...
Kyle Polich with guest Dan Kahan author
28.09.2018

False Discovery Rates

A false discovery rate (FDR) is a methodology that can be useful when struggling with the problem of multiple comparisons. In any experiment, if the experimenter checks more than one dependent variable, then they are making multiple comparisons. Natura...
21.09.2018

Deep Fakes

Digital videos can be described as sequences of still images and associated audio. Audio is easy to fake. What about video? A video can easily be broken down into a sequence of still images replayed rapidly in sequence. In this context, videos are simp...
Kyle Polich with guest Siwei Lyu author
14.09.2018

Fake News Midterm

In this episode, Kyle reviews what we've learned so far in our series on Fake News and talks briefly about where we're going next.
7.09.2018

Quality Score

Two weeks ago we discussed click through rates or CTRs and their usefulness and limits as a metric. Today, we discuss a related metric known as quality score. While that phrase has probably been used to mean dozens of different things in different cont...
31.08.2018

The Knowledge Illusion

Kyle interviews Steven Sloman, Professor in the school of Cognitive, Linguistic, and Psychological Sciences at Brown University. Steven is co-author of The Knowledge Illusion: Why We Never Think Alone and Causal Models: How People Think about the World...
Kyle Polich with guest Steven Sloman author
24.08.2018

Click Through Rates

A Click Through Rate (CTR) is the proportion of clicks to impressions of some item of content shared online. This terminology is most commonly used in digital advertising but applies just as well to content websites might choose to feature on their hom...
17.08.2018

Algorithmic Detection of Fake News

The scale and frequency with which information can be distributed on social media makes the problem of fake news a rapidly metastasizing issue. To do any content filtering or labeling demands an algorithmic solution. In today's episode, Kyle interviews...
Kyle Polich with guests Mike Tamir and Kai Shu author
10.08.2018

Ant Intelligence

If you prepared a list of creatures regarded as highly intelligent, it's unlikely ants would make the cut. This is expected, as on an individual level, ants do not generally display behavior that most humans would regard as intelligence. In fact, it mi...
Kyle Polich with guest Deborah Gordon author
3.08.2018

Human Detection of Fake News

With publications such as "Prior exposure increases perceived accuracy of fake news", "Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning", and "The science of fake news", Gordon ...
Kyle Polich with guest Gordon Pennycook author
27.07.2018

Spam Filtering with Naive Bayes

Today's spam filters are advanced data driven tools. They rely on a variety of techniques to effectively and often seamlessly filter out junk email from good email. Whitelists, blacklists, traffic analysis, network analysis, and a variety of other tool...
20.07.2018

The Spread of Fake News

How does fake news get spread online? Its not just a matter of manipulating search algorithms. The social platforms for sharing play a major role in the distribution of fake news. But how significant of an impact can there be? How significantly can bot...
Kyle Polich and Filippo Menczer author
13.07.2018

Fake News

This episode kicks off our new theme of "Fake News" with guests Robert Sheaffer and Brad Schwartz. Fake news is a new label for an old idea. For our purposes, we will define fake news information created to deliberately mislead while masquerading as a ...
Kyle Polich with Robert Shaeffer and A. Brad Schwartz author
11.07.2018

Dev Ops for Data Science

We revisit the 2018 Microsoft Build in this episode, focusing on the latest ideas in DevOps. Kyle interviews Cloud Developer Advocates Damien Brady, Paige Bailey, and Donovan Brown to talk about DevOps and data science and databases. For a data scienti...
Kyle Polich with Damien Brady, Paige Bailey, and Donovan Brown author
6.07.2018

First Order Logic

Logic is a fundamental of mathematical systems. It's roots are the values true and false and it's power is in what it's rules allow you to prove. Prepositional logic provides it's user variables. This episode gets into First Order Logic, an extension t...
29.06.2018

Blind Spots in Reinforcement Learning

An intelligent agent trained in a simulated environment may be prone to making mistakes in the real world due to discrepancies between the training and real-world conditions. The areas where an agent makes mistakes are hard to find, known as "blind spo...
Kyle Polich with guest Ramya Ramakrishnan author
22.06.2018

Defending Against Adversarial Attacks

In this week’s episode, our host Kyle interviews Gokula Krishnan from ETH Zurich, about his recent contributions to defenses against adversarial attacks. The discussion centers around his latest paper, titled “Defending Against Adversarial Attacks by L...
15.06.2018

Transfer Learning

On a long car ride, Linhda and Kyle record a short episode. This discussion is about transfer learning, a technique using in machine learning to leverage training from one domain to have a head start learning in another domain. Transfer learning has so...
Kyle Polich author
8.06.2018

Medical Imaging Training Techniques

Medical imaging is a highly effective tool used by clinicians to diagnose a wide array of diseases and injuries. However, it often requires exceptionally trained specialists such as radiologists to interpret accurately. In this episode of Data Skeptic,...
1.06.2018

Kalman Filters

Thanks to our sponsor Galvanize A Kalman Filter is a technique for taking a sequence of observations about an object or variable and determining the most likely current state of that object. In this episode, we discuss it in the context of tracking our...
Kyle Polich and Linh Da Tran author
25.05.2018

AI in Industry

There's so much to discuss on the AI side, it's hard to know where to begin. Luckily,  Steve Guggenheimer, Microsoft’s corporate vice president of AI Business, and Carlos Pessoa, a software engineering manager for the company’s Cloud AI Platform, talke...
18.05.2018

AI in Games

Today's interview is with the authors of the textbook Artificial Intelligence and Games.
11.05.2018

game-theory

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Kyle Polich and Linh Da Tran author
4.05.2018

The Experimental Design of Paranormal Claims

In this episode of Data Skeptic, Kyle chats with Jerry Schwarz from the Independent Investigations Group (IIG)'s SF Bay Area chapter about testing claims of the paranormal. The IIG is a volunteer-based organization dedicated to investigating paranormal...
Kyle Polich with guest Jerry Schwartz from the Independent Investigations Group author
27.04.2018

Winograd Schema Challenge

Our guest this week, Hector Levesque, joins us to discuss an alternative way to measure a machine’s intelligence, called Winograd Schemas Challenge. The challenge was proposed as a possible alternative to the Turing test during the 2011 AAAI Spring Sym...
Kyle Polich with guest Hector Levesque author
20.04.2018

The Imitation Game

This week on Data Skeptic, we begin with a skit to introduce the topic of this show: The Imitation Game. We open with a scene in the distant future. The year is 2027, and a company called Shamony is announcing their new product, Ada, the most advanced ...
13.04.2018

Eugene Goostman

In this episode, Kyle shares his perspective on the chatbot Eugene Goostman which (some claim) "passed" the Turing Test. As a second topic Kyle also does an intro of the Winograd Schema Challenge.
Kyle Polich author
6.04.2018

The Theory of Formal Languages

In this episode, Kyle and Linhda discuss the theory of formal languages. Any language can (theoretically) be a formal language. The requirement is that the language can be rigorously described as a set of strings which are considered part of the langua...
Kyle Polich and Linh Da Tran author
30.03.2018

The Loebner Prize

The Loebner Prize is a competition in the spirit of the Turing Test.  Participants are welcome to submit conversational agent software to be judged by a panel of humans.  This episode includes interviews with Charlie Maloney, a judge in the Loebner Pri...
Kyle Polich with guests Charlie Maloney and Bruce Wilcox author
23.03.2018

Chatbots

In this episode, Kyle chats with Vince from iv.ai and Heather Shapiro who works on the Microsoft Bot Framework. We solicit their advice on building a good chatbot both creatively and technically. Our sponsor today is Warby Parker.
Kyle Polich with guests Vince Lynch and Heather Shapiro author
16.03.2018

The Master Algorithm

In this week’s episode, Kyle Polich interviews Pedro Domingos about his book, The Master Algorithm: How the quest for the ultimate learning machine will remake our world. In the book, Domingos describes what machine learning is doing for humanity, how ...
Kyle Polich with guest Pedro Domingos author
9.03.2018

The No Free Lunch Theorems

What's the best machine learning algorithm to use? I hear that XGBoost wins most of the Kaggle competitions that aren't won with deep learning. Should I just use XGBoost all the time? That might work out most of the time in practice, but a proof exists...
Kyle Polich and Linh Da Tran author
2.03.2018

ML at Sloan Kettering Cancer Center

For a long time, physicians have recognized that the tools they have aren't powerful enough to treat complex diseases, like cancer. In addition to data science and models, clinicians also needed actual products — tools that physicians and researchers c...
Kyle Polich with guests Alex Grigorenko and Iker Huerga from Memorial Sloan Kettering Cancer Center author
23.02.2018

Optimal Decision Making with POMDPs

In a previous episode, we discussed Markov Decision Processes or MDPs, a framework for decision making and planning. This episode explores the generalization Partially Observable MDPs (POMDPs) which are an incredibly general framework that describes mo...
Kyle Polich and Linhda Tran author
16.02.2018

AI Decision-Making

Making a decision is a complex task. Today's guest Dongho Kim discusses how he and his team at Prowler has been building a platform that will be accessible by way of APIs and a set of pre-made scripts for autonomous decision making based on probabilist...
Kyle Polich and Dongho Kim of prowler.io author
9.02.2018

[MINI] Reinforcement Learning

In many real world situations, a person/agent doesn't necessarily know their own objectives or the mechanics of the world they're interacting with. However, if the agent receives rewards which are correlated with the both their actions and the state of...
Kyle Polich and Linh Da Tran author
2.02.2018

Evolutionary Computation

In this week’s episode, Kyle is joined by Risto Miikkulainen, a professor of computer science and neuroscience at the University of Texas at Austin. They talk about evolutionary computation, its applications in deep learning, and how it’s inspired by b...
Kyle Polich with guest Risto Miikkulainen author
26.01.2018

[MINI] Markov Decision Processes

Formally, an MDP is defined as the tuple containing states, actions, the transition function, and the reward function. This podcast examines each of these and presents them in the context of simple examples.  Despite MDPs suffering from the curse of d...
Kyle Polich and Linh Da Tran author
19.01.2018

Neuroscience Frontiers

Last week on Data Skeptic, we visited the Laboratory of Neuroimaging, or LONI, at USC and learned about their data-driven platform that enables scientists from all over the world to share, transform, store, manage and analyze their data to understand n...
12.01.2018

Neuroimaging and Big Data

Last year, Kyle had a chance to visit the Laboratory of Neuroimaging, or LONI, at USC, and learn about how some researchers are using data science to study the function of the brain. We’re going to be covering some of their work in two episodes on Data...
Kyle Polich, Dr. Arthur Toga, Dr. Meng Law, Farshid Sepherband, Ryan Cabeen author
5.01.2018

The Agent Model of Artificial Intelligence

In artificial intelligence, the term 'agent' is used to mean an autonomous, thinking agent with the ability to interact with their environment. An agent could be a person or a piece of software. In either case, we can describe aspects of the agent in a...
Kyle Polich and Linh Da Tran author
29.12.2017

Artificial Intelligence, a Podcast Approach

This episode kicks off the next theme on Data Skeptic: artificial intelligence.  Kyle discusses what's to come for the show in 2018, why this topic is relevant, and how we intend to cover it.
Kyle Polich author
22.12.2017

Holiday reading 2017

We break format from our regular programming today and bring you an excerpt from Max Tegmark's book "Life 3.0".  The first chapter is a short story titled "The Tale of the Omega Team".  Audio excerpted courtesy of Penguin Random House Audio from LIFE 3...
Kyle Polich with a reading by Rob Shapiro from Max Tegmark's book author
15.12.2017

Complexity and Cryptography

This week, our host Kyle Polich is joined by guest Tim Henderson from Google to talk about the computational complexity foundations of modern cryptography and the complexity issues that underlie the field. A key question that arises during the discussi...
Kyle Polich with guest Tim Henderson author
14.12.2017

Mercedes Benz Machine Learning Research

This episode features an interview with Rigel Smiroldo recorded at NIPS 2017 in Long Beach California.  We discuss data privacy, machine learning use cases, model deployment, and end-to-end machine learning.
Kyle Polich with guest Rigel Smiroldo author
8.12.2017

[MINI] Parallel Algorithms

When computers became commodity hardware and storage became incredibly cheap, we entered the era of so-call "big" data. Most definitions of big data will include something about not being able to process all the data on a single machine. Distributed co...
Kyle Polich and Linhda Tran author
1.12.2017

Quantum Computing

In this week's episode, Scott Aaronson, a professor at the University of Texas at Austin, explains what a quantum computer is, various possible applications, the types of problems they are good at solving and much more. Kyle and Scott have a lively dis...
Kyle Polich with guest Scott Aaronson author
28.11.2017

Azure Databricks

I sat down with Ali Ghodsi, CEO and found of Databricks, and John Chirapurath, GM for Data Platform Marketing at Microsoft related to the recent announcement of Azure Databricks. When I heard about the announcement, my first thoughts were two-fold.  Fi...
Kyle Polich with guests Ali Ghodsi of Databricks and John Chirapurath of Microsoft author
24.11.2017

[MINI] Exponential Time Algorithms

In this episode we discuss the complexity class of EXP-Time which contains algorithms which require $O(2^{p(n)})$ time to run.  In other words, the worst case runtime is exponential in some polynomial of the input size.  Problems in this class are even...