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Since 1969, the Washington Monthly has brought a sharp eye to politics, policy and the business of government. Our mission: Champion democracy, support good governance, and promote American opportunity for all.
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"If you bust your butt, you should get ahead" | Jim Kessler
The think tank Third Way recently released what it calls a "new economic bargain" with the middle class. It's premised on the idea that "if you bust your butt, you should get ahead," says Executive Vice President for Policy Jim Kessler.
The organization proposes a slate of 20 practical ideas it says will significantly improve the lives of middle-class Americans. Among these proposals: cheaper used car loans and a universal pension.
Host: Anne Kim, Washington Monthly
Guest: Jim Kessler, Third Way
Chapters
00:00 Introduction to the agenda and its importance
01:59 The changing perception of the middle class
04:04 Historical context and the evolution of middle class policies
06:09 Core message: work should lead to getting ahead
08:01 Proposal for federal guarantees on used car loans
10:01 Work as a pathway to wealth and retirement security
12:00 Party branding and electoral challenges
13:58 Comparison with other policy proposals and think tanks
16:09 Feasibility of big reforms like Medicare for All
18:56 Addressing criticisms of incrementalism
21:04 The impact of proposed policies on wealth and inequality
23:05 Shared priorities across different political agendas
23:58 Optimism for Democratic electoral prospects in 2028
7 Oct 2026
Is political polling broken? | Stefan Hankin
A veteran pollster points to several factors wrecking polling’s reputation, including overhyped results and a sea of low-quality polls.
Political polling has suffered some embarrassing failures (https://www.pbs.org/newshour/show/why-primary-polls-appear-to-be-so-inaccurate-this-year) this year.
In Michigan’s Democratic Senate primary, polls predicted a blowout for Abdul El-Sayed; he won by less than a percentage po (https://www.nytimes.com/interactive/2026/08/04/us/elections/results-michigan-us-senate-primary.html)int. In Wisconsin, polls showed Democratic SocialistFrancesca Hong enjoying double-digit leads (https://www.nytimes.com/2026/08/12/us/politics/crowley-hong-wisconsin-governor-primary-polls.html) in the gubernatorial primary; she narrowly lost to David Crowley.
In truth, polls have always been unreliable.
Longtime Democratic pollster Stefan Hankin, founder and CEOof Lincoln Park Strategies, explains the myriad of challenges currently facing, including a lack of enforceable professional standards to prevent bad polls from getting press.
Host: Anne Kim, Washington Monthly
Guest: Stefan Hankin, Lincoln Park Strategies
Chapters
00:00 Introduction to polling failures in recent elections
02:12 What makes a good, trustworthy poll?
03:01 Sample size recommendations for state-wide polls
04:09 The difficulty of predicting likely voters
05:47 How pollsters select voter samples
07:36 Response rates and reaching respondents
08:38 Are polls becoming less reliable?
12:02 Lack of enforcement in polling standards
12:56 What went wrong in Michigan and Wisconsin
15:43 Are polls overselling their accuracy?
19:32 Prediction markets versus polls
22:09 How much should we trust polls for November?
24:22 How to responsibly interpret polling data
28:10 The future of polling technology and methods
29:45 The unpredictability of human behavior and polling
30 Sept 2026
AI's Anti-Woman Problem and How to Fix It | Shubhi Rao
The CEO of the world’s first “female-forward” AI startuphas a plan for tackling gender bias in artificial intelligence.
Host: Anne Kim, Washington Monthly
Guest, Shubhi Rao, CEO and Founder, Uplevyl
Chapters
00:00 Introduction to AI bias and societal influence
03:00 How large language models are trained and their data sources
07:04 Societal biases reflected in AI, especially regarding gender
12:03 Impact of data erasure on women-related research and information
19:12 Uplevyl's approach to building specialized vertical LLMs
22:08 Differences between vertical LLMs and commercial models
25:09 Policy implications and standardization in AI development
27:02 Advice for users to recognize and mitigate bias in AI responses
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