AT Policy Pilot CP - Michigan 7 2023 BFHGR

Aff Answers
General Answers
2AC --- Links to Ptix
CP wont shield backlash --- if they win the plan is unpopular, the cp is as well
Chien ‘19
(Colleen V. Chien, Justin D'Atri Visiting Professor of Business Law, Columbia Law School; Professor, Santa Clara University School of Law; 2013-2015 White House Senior Advisor, Innovation and Intellectual Property, “Rigorous Policy Pilots: Experimentation in the Administration of the Law, July, 2019, “104 Iowa L. Rev. 2313,” pg lexis//um-ef)
At the same time, as described above, rigorous experimentation will neither remove the burdens of ensuring an adequate nexus to a legitimate governmental objective, nor absolve an agency of procedural compliance with notice and comment, nor shield agency from scrutiny. When the stakes are high and agency action is likely to have material consequences for stakeholders, experimental evidence, like other evidence, is likely to be contested and challenged. While on one hand, experimental evidence can create a shared experience, on the other hand, stakeholders and even agencies are likely to interpret evidence in the manner that advances their interests. 135Matters of institutional competence may come into play if the court is unsure how to evaluate an an agency's experimental design or interpretation of experimental results.
BI Pilot Fails
A basic income pilot program is severely limited.
Standing ’21 [Guy; June 25; Professorial Research Associate at SOAS, University of London, and a founder and co-President of the Basic Income Earth Network (BIEN), Director of the Socio-Economic Security Programme of the International Labour Organisation, Former chairholder of Universities of Bath and Monash (Australia); “Basic Income Pilots: Uses, Limitations and Design Principles,” https://doi.org/10.1515/bis-2021-0021, WWIS]
Determining the impact of a basic income requires comparing outcomes, both with the behaviour and attitudes of people beforehand (before the ‘treatment’ began) and with ‘control groups’, otherwise similar, who do not receive the ‘treatment’ or come under the policy. This is to ensure that outcomes are the result of the basic income and not a change coming from the outside.
While randomised control trials (RCTs) are currently in vogue, they have severe limitations when it comes to evaluating basic income. The principle behind RCTs, as the name implies, is that those receiving the ‘treatment’ should be selected ‘randomly’ from a wider population, and the control group should also be selected ‘randomly’. This would typically mean listing households in an area and drawing a sample, so that one family (or individual within a family) would receive the basic income while the family next door would not.
Apart from the risk of generating inter-community and inter-familial tensions, one likely outcome would be some sharing of the basic income between households and between family members, on a non-random basis. This would negate the universality of the basic income, dilute its impact and make it hard to evaluate outcomes. In the Indian pilot in Madhya Pradesh, 18 similar villages were selected randomly from a wide area: in eight of these, everyone received the basic income and in the remaining 12 villages no one did. It was thus possible to explore a range of effects, both at micro-level and community level, including attitudinal and behavioural changes.
Pilots Don’t Spill-Over
Basic income pilots will not result in policy change---doesn’t spill over to a UBI.
Taylor ’22 [Chris; April 19; Academic director at Cardiff University Social Sciences Research Park (SPARK), Cardiff University; “Three reasons universal basic income pilots haven’t led to policy change – despite their success,” https://www.globalgovernmentforum.com/three-reasons-universal-basic-income-pilots-havent-led-to-policy-change-despite-their-success/, WWIS]
But none of the experiments have (so far) ended with the implementation of basic income as a policy, by keeping the pilot going or rolling it out to wider populations. The International Public Policy Observatory (of which The Conversation is a partner), in collaboration with the Institute of Policy Research at the University of Bath, recently examined 38 experiments across Europe, North America and Asia (in countries that already had established welfare systems) and found three main reasons why the effort ended with the pilot.
1. Gaps in evidence
Supporters of universal basic income usually point to a wide range of benefits to those who receive the payment, their family and their wider community. But collecting evidence on all possible outcomes has been difficult to achieve.
The complex designs of basic income pilots have made it difficult to show whether improvements in people’s lives are due to the introduction of a basic income or other factors. No two basic income pilots look the same, so the outcomes of one pilot are rarely the same in another. Keeping pilots as simple as possible and identifying the criteria for success prior to their introduction would strengthen the case for keeping the schemes going.
2. Short-term thinking
We found that most basic income experiments were intended to be just that – experiments. Few, if any, schemes were launched with a clear understanding of how they would be fully implemented if deemed successful. Many schemes broke down because the necessary fiscal and legal requirements for further roll-out did not exist.
If those designing the experiments do not see the problem as long term and systemic, then they will inevitably take a short-term view about any experiment and what they hope to learn from it.
Future experiments should be designed so that if they are found to be successful they can continue to run.
This might mean designing a scheme that will only benefit a small, well-defined group for a short and specific period of time. The scheme for care leavers in Wales is a good example of this. It is designed to target a particular group of vulnerable young people at a key point in their life.
The resulting benefit is only for a short period (when they are 18-20 years old) but at a time in their lives when we might expect to see the most advantage for minimal cost. The scheme can continue to run for new cohorts of care leavers after the pilot without the overall costs increasing.
3. Politics and public understanding
Despite the large number of pilots over the last 50 years, universal basic income is still highly controversial. Giving “free” money to people without conditions is very sensitive, particularly to people who work to earn money and pay their taxes.
Improving the public understanding and support of basic income remains a challenge. Pilots need to demonstrate how basic income benefits the whole of society, as well as those who receive the payment. Improving someone’s immediate wellbeing, for example, leads to less dependency on welfare benefits, lower levels of crime and reduced illness.
The public also needs to understand why people deserve to receive a basic income. Most basic income pilots are for the unemployed, and there is a fear that providing a guaranteed income will only continue their economic inactivity.
Evidence from previous pilots on this specific issue is mixed. Some people who receive basic income continue to remain unemployed, but for others it provides the necessary foundations for getting employment.
Many pilots have shown a marginal benefit of increased employment. But the continued presence of unemployed people in receipt of basic income, however small in number, undermines the public’s confidence in such a policy.
One solution is to target basic income at other groups of vulnerable people, where perhaps the public’s understanding of the challenges they face are greater to begin with. Again, the Wales example is a good one. While young care leavers are likely to be unemployed, their participation in the scheme is not defined by this. The public is also likely to have greater empathy for young adults who experienced difficult childhoods.
COVID and basic income
The pandemic has led to growing calls and public support for universal basic income. In the UK, a petition with 114,574 signatures triggered a parliamentary debate on the introduction of universal basic income to help families during the pandemic.
Experiments have shown the wide range of benefits such a policy could have, but few have been designed to provide long-term benefits or to fill the evidence gaps that remain. If policymakers continue to design basic income pilots without addressing these issues then they are likely to repeat the same mistakes. In doing so, they may even bolster their opponents’ arguments that basic income cannot work.
2AC --- Pilots Fails
Pilot program causes delays and uncertainty BUT has no net benefit.
Jon Western 12. Carol Hoffmann Collins '63 Professor of International Relations @ Mount Holyoke. “Can’t stop thinking about tomorrow…” https://duckofminerva.com/tag/forecasting
Michael Horowitz and Philip Tetlock have an interesting piece in Foreign Policy that examines the record on long-range forecasting of global events — 15 – 20 years into the future. They acknowledge the inherent difficulties of such a projections, but still wonder:
whether there are not ways of doing a better job — of assigning more explicit, testable, and accurate probabilities to possible futures. Improving batting averages by even small margins means the difference between runner-ups and World Series winners — and improving the accuracy of probability judgments by small margins could significantly contribute to U.S. national security.
Overall, I like the piece, but I do wonder about a couple of the basic premises and their prescription.
1. Would improving the accuracy of probability judgments actually enhance US national security? I’m not convinced. And, unfortunately, Horowitz and Tetlock don’t unpack this claim. They do acknowledge, and I agree, that improving accuracy would be difficult and it would only be improvements on the margins. The world is getting more complex, not less. It is more dynamic, not less. New and more actors in the international system interacting with greater frequency, more intensity, and faster speeds means that there is a constantly changing strategic environment in which actors act and react — and continue to change the strategic environment. In short, minor improvements in accuracy just might do anything because on whole everything is getting more complex.
2. Is accuracy the right metric? Even if we did have a better understanding (or thought we did) of the future, any policy calibrations made today on the basis of what that future might look like, could alter the future in ways that deviate from the accuracy of the long-range forecasting. In this sense, accuracy may well be the wrong metric.
3. Is there a downside in trying to get better? Maybe. Horowitz and Tetlock conclude:
Even if we were 80 percent or 90 percent confident that there is no room for improvement — and the Global Trends reports are doing as good a job as humanly and technically possible at this juncture in history — we would still recommend that the NIC conduct our proposed experiments. When one works within a government that routinely makes multibillion-dollar decisions that often affect hundreds of millions of lives, one does not have to improve the accuracy of probability judgments by much to justify a multimillion-dollar investment in improving accuracy.
Again, I think there is utility in long-range forecasting exercises, I’m just not sure I see any real benefits from improved accuracy on the margins. There may actually be some downsides. First, a “multi-million dollar investment” (they don’t tell us exactly how much) is still money and it may be a waste time and money to throw even more resources at an effort that is principally of interest only to the participants. Do policymakers really get much from projects like Global Trends or other long-range forecasts — and would they get added benefits from marginal improvements in accuracy? They already have their own biases and perceptions of the future — do these exercises have any real influence?
Second, what if we spend more time, money, and other resources to enhance those capabilities such that it alters decision-makers’ perceptions and gives them an unfounded sense of accuracy, i.e, that they come to see long-range forecasting as producing accurate or realistic futures? We may get a whole host of policy reactions that are unnecessary, wrong, and counterproductive based on what are still probabilistic outcomes.
---Pilot Projects fail
Pilot Projects are too costly---makes them less effective.
Camille Fink, 19. Freelance writer/editor and communications consultant based in Chicago. 2019. “The Problem with Pilot Programs.” https://www.planetizen.com/news/2019/09/106007-problem-pilot-programs
Pilots—for programs ranging from a new model of fire engine to teen pregnancy prevention efforts—are an accepted management technique almost everywhere. Unfortunately, there are lots of ways to get tripped up by them," write Katherine Barrett and Richard Greene.
One issue is that residents may not realize that the infrastructure or service is part of a pilot program that could eventually go away, they note. "So, if the ultimate decision is made that permanently implementing the pilot program would be too expensive, those who’ve enjoyed the benefits of the new service will lose it."
Pilot programs can also be costly and difficult to evaluate, making them a less effective policy and planning tool. In addition, the post-pilot next steps are not always clear, say Barrett and Greene. "Many observers are particularly concerned that a pilot program that is very successful for a portion of the city, county or state—geographically or demographically—may not be scalable to the entire entity, especially if the pilot program isn’t truly representative."
10 reasons pilot programs fail.
Ann Latham, 15. Contributor to Forbes. “10 Reasons Pilot Programs Fail And What To Do About It.” https://www.forbes.com/sites/annlatham/2015/12/20/10-reasons-pilot-programs-fail-and-what-to-do-about-it/?sh=2d3af5c14378.
Ready, Aim, Fire" is so old-fashioned. Careful, thorough, risk averse planners simply need not apply. This fast paced, action oriented world demands a lot less "readying" and "aiming." Pilot programs are a great response. Until they succumb to these common ailments:
1. Collaboration killers
If your goal is results, you need everyone driving toward those results and partnering for success. When you set up a pilot program, you shift the focus from achieving results to judging the program. People who need to be steadfast collaborators become observers and critics instead. An "us vs. them" mentality ensues and you won't get the partnership you desperately need to succeed.
2. Discouraging persistence
Dogged determination drives more projects across the finish line than any other force. Pilots rarely generate that level of determination. Instead, a noble champion and a fan or two are often seen slaving away while others dismiss the work as "just a pilot" - a short term, temporary, half-hearted inconvenience.
3. Too narrow to succeed
In an effort to create a well defined pilot, boundaries are drawn around people and systems. Unfortunately, these often exclude factors critical to success. Like the boss who needs to set a good example, hold people accountable, and reward desired behaviors.
4. The low hanging fruit
Too often pilots focus on the easy stuff. They fix the low hanging fruit and declare success. The tough issues remain. Year after year after year.
5. "This too shall pass."
Employees who have witnessed failed pilots and abandoned initiatives have learned that business-as-usual is often the easiest path. If they drag their feet and keep their heads down, management will give up and move on. As usual. Life will return to normal.
6. Undermine the goal
When the going gets tough, it is natural to regroup. Unfortunately, an improvement effort can undermine the goal when it is the method that needs to be changed. Take meetings, for example. Books, articles, and the Internet are loaded with techniques, mostly misguided, for improving meetings. Most companies have tried multiple times to improve results. Nothing seems to make much difference, but instead of recognizing the fundamental fallacy in those methods, they give up on the goal itself. Thus, incredibly wasteful meetings continue and people convince themselves that they aren't as bad as they are.
7. Too trivial to be convincing
My favorite is the pilot that succeeds gloriously but achieves nothing because it was shunted off to an "unimportant" group where everything is seen as simple. It's like proving that a drug works on cockroaches and then expecting people to give it to their children.
8. Omits the hardest part
A quick pilot that opens eyes, teaches a few new skills, and develops a new process is great for generating energy and enthusiasm. At least temporarily. If a pilot concludes before new behaviors become habits, old habits will reign, especially once the first kink is encountered.
9. Only works when things are slow
If you wait until a slow period to try something new, All you'll learn is that it can work in a slow period. You won't learn much and you won't create believers.
10. Abdication of responsibility!
2AC --- CP Wont Scale-up
The cp fails --- will be rejected and wont spill-up
Chien ‘19
(Colleen V. Chien, Justin D'Atri Visiting Professor of Business Law, Columbia Law School; Professor, Santa Clara University School of Law; 2013-2015 White House Senior Advisor, Innovation and Intellectual Property, “Rigorous Policy Pilots: Experimentation in the Administration of the Law, July, 2019, “104 Iowa L. Rev. 2313,” pg lexis//um-ef)
The previous Part addresses legal challenges to rigorous policy pilots. However, significant practical and institutional challenges to rigorous piloting will often attend. Recent research has found that people tend to view as inappropriate pilots that purport to randomize a treatment even when the underlying treatment is unobjectionable, 136suggesting that buy-in of the [*2336] relevant population, if required, will require education and communication. More upfront work is also required to make explicit the assumptions behind an intervention, and then to develop a strategy for testing them. Agencies carrying out rigorous tests must marshal resources, data, statistical expertise, support for departing from the status quo, and explanations for skeptics. 137There often will be no agreed upon measure of success. Even when there is, attrition, changed circumstances, poor design or a host of other factors can lead to a lack of inconclusive or null results. The results may be rejected. For example, in their review of the 50 or so randomized experiments in U.S. law that have ever been conducted, mostly in the field of criminal law and judicial procedure, Greiner and Matthews found a major problem to be the refusal of judges and lawyers to accept experimental results that did not jive with their sense of the "right answer." 138
2AC --- CP freaks-out stakeholders
Uncertainty of the cp freaks out stakeholders --- undermines support for the CP
Chien ‘19
(Colleen V. Chien, Justin D'Atri Visiting Professor of Business Law, Columbia Law School; Professor, Santa Clara University School of Law; 2013-2015 White House Senior Advisor, Innovation and Intellectual Property, “Rigorous Policy Pilots: Experimentation in the Administration of the Law, July, 2019, “104 Iowa L. Rev. 2313,” pg lexis//um-ef)
While a voluntary, limited or temporary pilot will have less impact than a mandatory, agency-wide, or permanent practice, there's also a risk that the [*2331] uncertainty associated with a temporary program will unsettle stakeholders and result in more speculative and premature reactions than would be elicited by a more formed 

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