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Wisconsin’s Election Debacle a Cautionary Tale for States

Wisconsin last week became the unlucky test subject for a slew of last-minute election reforms. The state was the first to conduct a major election since stay at home orders have gone into effect across much of the country in response to COVID-19. Despite election administrators’ considerable effortsthe credibility of the election was marred by unprecedented polling place closureslong lines to vote, problems processing absentee ballots, partisan court rulings, and contrary messaging from the governor, courts, and legislature. 

States must learn from Wisconsin’s experience and pay close attention to the following issues that will continue to test the legitimacy of elections throughout 2020.

Absentee Ballot Concerns 

Wisconsin localities saw astronomically long lines at polling places last Tuesday, in direct contradiction to social distancing guidelines. Both Milwaukee and Green Bay saw wait times of over two hours to vote, and pockets of even longer waits existed throughout the state. 

The risk of standing among so many people to vote was particularly acute for high risk groups with comorbidities, and for persons with disabilities who may struggle to stand for long periods of time.  

Furthermore, these risks were not equally distributed. BPC’s report on voting lines in 2018 found that communities with a high percentage of minority and low-income voters already wait in much longer lines than others. That was with a full slate of polling places; the problem of long waits is compounded when the mere existence of lines exposes voters to a deadly disease.  

The long lines were the result of a shortage of poll workers, which necessitated polling place closures. In the lead up to Election Day, local election officials warned that poll workers feared for their health and would not show up on Election Day. As a result, Milwaukee, which usually has 180 polling places, deployed just five voting centers where any voters in the city could cast their ballot. 

Poll worker recruitment will continue to be a problem throughout this election cycle. The Election Assistance Commission found that over 56% of poll workers were over the age of 60 in 2016. Additionally, nearly 65% of jurisdictions have difficulty obtaining sufficient numbers of poll workers under normal circumstances, let alone during a pandemic. 

Limited access to polling places and the disproportionate impact on some demographic groups will call into question the legitimacy of this election and others that take place with similar issues during this pandemic. 
Wisconsin officials attempted to alleviate pressure at the polls on Election Day by pushing voters to use the state’s no-excuse absentee voting option. Voters responded by applying for absentee ballots in unprecedented numbers. Preliminary totals already show upwards of a 313% increase in absentee ballots returned compared to the 2016 presidential preference primary 

Ramping up absentee voting from a small portion of the ballots cast to the majority of ballots cast in a short timeline is no easy taskFirst, the tidal wave of absentee ballot requests overwhelmed election officials. Issuing an absentee ballot is time consuming and difficult to automate, and officials lacked the staff to handle a 300% increase in applications, which caused a huge backlog in sending ballots in time for voters to return them by Election Day.  

Many voters in line at polling places on Tuesday remarked that they had requested an absentee ballot, but never received it. This was the case for thousands of voters across Wisconsin, and it clearly demonstrates the logistical difficulties of ramping up absentee and voting by mail in a short timeframe.  

Second, rules for accepting absentee ballots shifted several times amidst ongoing court action in Wisconsin. These shifts caused the likely disenfranchisement of hundreds, if not thousands, of voters. 

The day prior to the scheduled election, Wisconsin Governor Tony Evers (D) signed an executive order declaring the election delayed and all in-person voting suspended. However, mere hours later, the Wisconsin Supreme Court reversed this decision and the following day’s election was back on.  

Luckily, Wisconsin Election Commission Administrator and BPC Task Force on Elections member Meagan Wolfe foresaw these back and forth actions and issued a forward-thinking recommendation to all of Wisconsin’s election officials following Gov. Evers’ executive order: continue as if the election is still happening 

The problem was further compounded by additional court action. In a separate suit also occurring in the days before the election, a federal judge ruled that absentee voting should be extended until April 13th and absentee ballots could be submitted without a witness signature. Subsequently, the 7th Circuit Court of Appeals ruled that all absentee ballots must have the witness signature, and the U.S. Supreme Court issued an opinion mandating that absentee ballots would be accepted through April 13th only if postmarked by the close of polls on April 7th 

The result of these reversals was additional confusion and the creation of a window in which voters who followed the rules in place at the time risked having their ballots revoked later. Voters who submitted their absentee ballots without a witness signature on the return envelope will not have their ballots counted. Making matters worse, these voters were not eligible to vote in person after the ruling because they had already received absentee ballots, even though those absentee ballots were invalided by the courts’ rulings. Additionally, voters who thought they had until April 13th to vote received their ballots too late to get them postmarked by the close of polls on Election Day. 

Moving forward, states should look to Wisconsin with at least one clear takeaway: make all decisions about election administration quickly and finally. Running an election should not be a guessing game about whose policy will ultimately prevail; instead, states must issue clear guidance about their elections if they want them to be perceived as legitimate. 

Can AI Accelerate Innovation?

Pivotal technologies have helped accelerate the discovery of other new technologies throughout history. For instance, the telescope powered the fields of astronomy and physics, while the microscope led to new innovations in the field of biology.

Artificial intelligence has the potential to be such a technology. For instance, in the field of material science, AI has already aided in the discovery of new materials for a broad range of applications including in clean energy, advanced electronics, and next generation aerospace technologies. A number of research funding agencies—including the National Science Foundation, the Department of Energy and the National Institute of Standards and Technology—have been exploring ways to expand the use of AI technologies to accelerate these discoveries. This suggests AI can greatly boost our understanding of the world and foster innovation beyond the realm of computer science.

AI Limitations

In thinking about innovation and ways to accelerate it, three interrelated challenges merit consideration:

  1. The Burden of Knowledge: The expertise necessary to make original contributions in a field is likely to grow the further we advance technologically, which suggests researchers will require more education and larger teams to innovate.
  2. Discovering Useful Combinations: Innovation often requires combining different inputs, data, and ideas, but it is difficult to discover what combinations are useful, especially as the amount of information available continues to grow.
  3. Risk and Uncertainty: The greater the risk and uncertainty around an R&D project, the more costly it becomes to finance.

These challenges are all currently present and will persist for the foreseeable future. However, AI provides a tool to help mitigate them:

  1. AI can help reduce the burden of knowledge by making knowledge more accessible. For example, many researchers have been using AI as a tool to more quickly gather and synthesize a large number of research papers, which can greatly speed up the literature review process.
  2. AI can help more quickly and efficiently find combinations that spur innovation. Some of the most pressing challenges today, including climate change, require multi-disciplinary approaches to innovation. The Advanced Research Projects Agency – Energy (ARPA-E) has recently invested in the development of AI tools which combine wider ranges of innovative concepts together which are capable of designing better photovoltaics, turbine blades, and power electronics to enable the decarbonization of the U.S. economy.
  3. AI can help more accurately calculate the risk of an R&D project, which can reduce financing cost and allow companies to more efficiently allocate resources. For instance, AI is being used by pharmaceutical companies to predict the likelihood of success for a drug development program. If successful, these efforts can reduce the cost of developing drugs, while improving patient outcomes.

Adapting Public Policy

AI offers many benefits toward boosting innovation, but it can be overhyped, potentially leading to counterproductive disillusionment. Therefore, it is important to provide a realistic assessment of its potential and highlight some of its limitations:

  1. AI can be bound by data limitations. A lack of good data can limit the effectiveness of AI and prevent it from reaching its full potential. For instance, an AI trying to discover medical treatments personalized to specific patients would be less effective if it has less data about different patients to train itself with.
  2. AI can be bound by the availability of computing power. Similar to data limitations, AI can be constrained by how much computing power it has to process data.
  3. The burden of knowledge can only be shrunk so much by AI. AI can help reduce the burden of knowledge for researchers, but there are limits to how much this can shrink. By analogy, internet search engines have made browsing for academic articles easier because people don’t have to go to a library and find articles manually, but one still needs to have a general sense of what they are looking for and how to weed through search results.
  4. There are limits to the types of combinations and innovations that AI is good at finding. This could result in a spurt of AI-based innovation at first, but a dramatic slowdown after the “low hanging fruit” are picked.
  5. AI cannot do everything in the creativity process. For instance, AI is currently not good at making causal inferences, so domain expertise will continue to be important in dealing with issues of causality. AI will be a tool to enable domain experts to work more efficiently, but experts still need to be experts.

Policymakers can help optimize the use of AI for driving innovation, but they need to ask the right questions. Several questions include:

  1. How can the government better incorporate AI into its R&D roadmaps?
  2. What can the government do to make datasets more accessible to university and public-sector researchers, while maintaining proper safeguards for sensitive information?
  3. Can public policy play a role in fostering the effective use of AI in R&D at the private sector and universities?
  4. How can we increase public and industry awareness about the potential (and limitations) of AI to boost the rate of innovation in the United States?

BPC Narrows “X-Date” Forecast to Early to Mid-October

BPC has narrowed its projection window for the debt limit “X Date,” when the federal government would not be able to pay all its bills in full and on time, to early to mid-October. This projection parallels the one released recently by the Congressional Budget Office, which reached a similar conclusion.

Source: BPC projections, U.S. Treasury Department financial data


The debt limit was reinstated on March 16, 2017, at $19.8 trillion. Treasury Secretary Steven Mnuchin immediately deployedextraordinary measures,” which are congressionally authorized maneuvers that allow for temporary additional borrowing so that the government can continue paying its bills. Because of the large federal deficit, if the debt limit is not increased or suspended, those extraordinary measures will run out in the coming months. Shortly thereafter, Treasury’s cash reserves will be depleted. Upon reaching that point, known as the “X Date,” the U.S. government will no longer have any means, aside from insufficient incoming revenues, by which to continue meeting its obligations.

BPC has updated its projection of the “X Date” after a review of the latest financial data for the federal government from the month of June, including the Treasury Department’s financial statements reporting the status of its extraordinary measures. Key to the forecast were the individual and corporate quarterly tax receipts due by June 15. Federal revenues have been lower than expected in recent months, possibly in part due to taxpayers shifting capital gains to future years in anticipation of lower tax rates through tax reform. This trend, among other factors, led to our updated projection that the “X Date” will fall in early to mid-October from the previous range of October to November.

It is important to note that predictions of federal spending and revenues can, and often do, miss the mark. The federal government’s balance sheet is too complex to project a specific day for the “X Date” with a high degree of certainty. Moreover, it could even come before or after BPC’s projection range, especially if unanticipated legislative or economic events were to occur.

That said, there is currently significant evidence to support an “X Date” within the early to mid-October period. The first few weeks of October have, historically speaking, tended to include large payments and net negative cash flows. These payments, which include Social Security, Medicare, Medicaid and other obligations, have contributed to an average $104 billion cash flow shortfall in October over the past five years. In addition to the regular, recurring payments, a large payment must be made on October 2 to the Military Retirement Trust Fund ($81 billion in 2016).

Monthly Net Operating Cash Flow

Source: U.S. Treasury Monthly Statements


BPC’s narrowed projection range and the similar CBO projection suggest that in order to definitively prevent serious economic consequences that could be associated with reaching the “X Date,” policymakers would need to take action on the debt limit well before October. With government funding (appropriations), health care, and several other pressing issues on tap, this could shape up to be a chaotic end to the fiscal year.  



Read further information on BPC’s Debt Limit Analysis.