Legislating Ignorance: Scientific Literacy, Political Partisanship, & the U.S. Economy

Comment

Share

Legislating Ignorance: Scientific Literacy, Political Partisanship, & the U.S. Economy

Historical evidence testifies to a causal relationship between scientific awareness and a nation’s socio-economic progress. This evidence stems from the era of the ancient Greeks to the European Age of Exploration and more recent advancements in American space travel and quantum physics. The inverse dynamic also holds true since nations that lack scientific development tend to face economic stagnation and an overall impoverished way of life.  Since the early 20th century, the U.S. has consistently breached numerous frontiers of scientific research and discovery. This approach led to a plethora of technological innovations and a thriving national economy. In recent years, however, there has been a decay in American scientific policy, especially with regards to research and development (R&D), as political loyalties lead to more partisan policymaking. Deconstructing the repercussions of scientifically regressive legislation on local economies demonstrates the consequences of civic scientific unawareness in the U.S. Doing so also highlights the dangers of partisanship in national science policymaking and emphasizes the necessity of scientific literacy for all citizens today. The effects of collective scientifically illiterate governance thus impoverishes both the immediate and future economic standing and prosperity of the United States.

Advancements in science and technology through federally-funded research demonstrate strong economic returns through technological innovation and workforce employment. The most powerful drivers of political decisions on national funding in the U.S. remain to be war and economic prosperity. Preserving national security fueled much of federal scientific research during most of the twentieth century with World War II and the Cold War driving the U.S. government to advance its scientific and technological frontiers on weaponry and defense. However, more recently economic growth has driven research funding, especially following the economic crises of the 1980s and late 2000s. Analyses and assessments by the NIH, OECD, and economists consistently find a correlation between drastic downturns in national economics and spikes in federal allocation towards R&D in following years. The 2008 federal stimulus package dedicated to revitalizing the American economy included sizeable expansions to research and development in spheres of scientific research not traditionally linked to economics at all—including biomedical research and nanotechnology—and investments in these fields soon began contributing to increasing national revenue and eliminating debt [1]. Contrary to popular opinion, the challenge to this system primarily occurs in periods of economic growth and prosperity, where the public and policymakers alike take the continual status of economic success for granted and begin to view scientific research as expendable. As Congressional appropriations begin to slash the percentage of federal allocations for research, local economies housing those research centers begin feeling the repercussions of these reductions. In addition to these immediate effects, the long-term aftermath of the under-prioritization of science includes plummeting payoffs from research. Current projects in research institutions are curtailed as funding begins to stagnate and the findings of these malnourished projects lack the potential to further discovery. In recent years, as the authority of science itself has come under attack, politicians find it increasingly easier to dismiss the scientific community’s recommendations as simply the advocacy of the rival political party. As legislators continue to prioritize partisan agendas over scientific authority, they subsequently place scientific research lower on the ranks of national policymaking, thus crippling the future growth and expansion of the American economy.

Prolonged and unpredictable timelines for returns on scientific funding to manifest encourages society to prioritize lucrative short-term industries over expanding alternative sustainable enterprises. However, the vast majority of American economic and industrial growth over the past century alone has ridden almost entirely on the wave of these scientific investments rather than short-term expenditures. Indeed, academic studies and analyses from the mid-20th century demonstrate that “an estimated 67 percent of the productivity growth in the United States from 1948 to 1973 was attributable to advances in applied knowledge, technology, and in the education and experience of the labor force” [3]. While progress in all of these operates on significantly lengthier timelines than most areas of public policy, the impact of these intangible investments on national economics alone over time far outweigh the fiscal returns of any expenditure made for short-term gain. Historical observation consistently witnesses this trend occurring throughout the trajectory of scientific discoveries funded by major global superpowers. From funding the research of electromagnetism in the 1800s to spearheading discoveries in quantum physics and space exploration in the last century, pursuing almost every groundbreaking scientific or technological advancement requires some degree of vision and long-term commitment from policymakers and governments to allow these discoveries to revolutionize society over prolonged timescales [4]. However, this phenomenon begins experiencing severe ideological complications when viewed through a contemporary political lens. With the recent influx of partisanship into science policy, politicians find it increasingly difficult to justify funding research clashing with established socio-political ideologies, especially those initiatives with no immediate returns in sight but rather promised benefits over a period extending farther than any congress member’s reelection timescale [5]. This myopic condition is especially true and even aggravated for those policymakers receiving significant financial backing from corporations and entities challenged by expansions to sustainable industries. Simple scientific consensus has been eliminated from forming the crux of discussions in science policy, as partisan loyalties and socio-political ideologies have begun to take precedence in Congress. When compounded with the expanded influence of financial sway in the political process, policymakers begin to neglect undertaking extended scientific and technological projects for the sake of appeasing their corporate campaign financers and gaining political points for the next election cycle.

By allowing partisan short-sightedness to take priority over scientific awareness, the U.S. weakens its role in future global markets founded on innovation. If we take historical evidence as an indicator of future trajectories, tomorrow’s economies will be founded on the scientific and technological progress of today. Although numerous short-term remedies for this issue exist within the political framework of the government, the definitive long-term solution lies in informing the public of the indispensability of scientific discovery and the necessity to maintain impartiality in formulating science policy. A public holding low regards for scientific research or awareness will inevitably elect representatives into office who introduce legislation rooted within either fundamental scientific unawareness or partisan science policy. Policy that will eventually go on to undermine and debilitate both local and national economies within the US and the larger global community as well.


References

  1. Rosenberg, Nathan. “Science, Invention and Economic Growth.” The Economic Journal, vol. 84, no. 333, 1974, pp. 90–108. JSTOR.

  2. “Sustaining a Competitive Edge in Innovation Through a World-Class Federal Science and Technology Workforce,” Fast Track Action Committee on the Federal Science and Technology Workforce. National Science and Technology Council, July 2016.

  3. Walberg, Herbert J. “Scientific Literacy and Economic Productivity in International Perspective.” Daedalus, The MIT Press, vol. 112, no. 2, 1983, pp. 1–28. JSTOR.

  4. Wright, Carroll D. “Science and Economics.” Science, vol. 20, no. 522, 1904, pp. 897–909. JSTOR.

  5. Blute, Marion. “The Growth of Science and Economic Development.” American Sociological Review, vol. 37, no. 4, 1972, pp. 455–464. JSTOR.

  6. Lee, Stuart, and Wolff-Michael Roth. “Science and the ‘Good Citizen’: Community-Based Scientific Literacy.” Science, Technology, & Human Values, vol. 28, no. 3, 2003, pp. 403–424. JSTOR.


Comment

Share


Hello Quantum Worlds!

Comment

Share

Hello Quantum Worlds!

Quantum computing has been projected as a sort of messiah to the technological plateau that humanity is experiencing. The general prevailing belief is that with the advent of QC, we will be able to do the impossible — break cryptographic codes, solve problems that have eluded computer scientists for years, and even occupy interstellar space.



This is what everyone has to offer when asked what quantum computing is:  “Well, these computers can tackle multiple problems at once. It’s because classical computers can only be in one state at a time — 0 or 1 — while quantum computers can be in both states at the same instant of time!”



The only problem with this explanation is that it is wrong, and misleading to say the very least.

No, quantum computers are NOT in the same state at the same time. At least not technically, and although we might be able to break cryptographic codes faster, we won’t be able to solve puzzles miraculously.



Justin Trudeau was asked to summarize[1] quantum computing and he summed it up better than any layman explanation would:


“Very simply…normal computers work, either there’s power going through a wire or not— a one, or a zero. They’re binary systems … What quantum states allow for is much more complex information to be encoded into a single bit…a quantum state can be much more complex than that, because as we know, things can be both particle and wave at the same time.”


He was careful not to use the term “can be in both states at the same time,” which is commendable because that is where the problem lies. It turns out that staying in two states is physically impossible. Rather, quantum computers fundamentally take advantage of the superposition principle in quantum mechanics which states that any particle can be assumed to be in all states until and unless observed. Upon observation, the particle randomly takes one of the states. In other words, quantum computers form entangled states[2] of 0 or 1, and stay in those states, which is vastly different from staying in two states at the same time. A geometric way to think about it is to think of 0 and 1 as only the poles of a sphere, and a “qubit” as any point on that sphere. Due to a multitude of these points, data of many orders of magnitude[3] more can be stored using the same number of qubits and classical bits.



While we may still be able to crack conventional cryptographic techniques much faster, it is because of this enormous capability to store more data and not because of duality of states. The class of problems known as non deterministic polynomial complexity or NP — problems that don’t seem to have polynomial time solution-getting algorithms — will unfortunately still remain unsolved,  because quantum computers don’t so much mathematically model a problem as physically model it; in theory, we let nature do the math for us, and just watch where the final state ends up. The newfound capability to break crypto sequences wouldn’t be a problem in the long run either, because there are ways to make it even more secure using quantum cryptography. In fact, Google has already begun testing[4] such techniques. Even current state of the art research cannot guarantee that the “speed-up” on computational problems we expect from quantum computing will happen for all problems. Recently, Ewin Tang from the University of Texas at Austin proved that one of the major advances in quantum computing was redundant[5] and can be achieved by classical computing, which set back the quantum industry by decades. Add to that to the fact that we are at least a decade away from the world’s first meaningful quantum computer, and we’ve been that way for more than a decade, the picture is not so rosy anymore.



But there’s more reason to be optimistic than dismal. Intel has already created 49 and 17 qubit processor chips[6] that offer a glimpse into the enormous potential of quantum computing. They demonstrably prove that most traditional solvable problems will be solved in milliseconds, compared to minutes in the traditional way. The only major hurdle for stable quantum computing remains to achieve absolute zero-like temperatures. Qubits require temperatures 250 times colder than outer space to sustain their wave-like behavior. Attempts to recreate those environments in today’s laptops have yielded little fruit, however, the news that major companies have already started preparing for a quantum future is reason enough to be optimistic. And while we may not have quantum computers in our pocket anytime soon, watch out for each quantum of progress they make.




References

  1. Morris, David Z (April 17, 2016). “Justin Trudeau Explains Quantum Computing, And the Crowd Goes Wild”. Fortune Magazine. http://fortune.com/2016/04/17/justin-trudeau-quantum-computing/

  2. Beall, Abigail and Reynolds, Matt (February 16, 2018). “What are quantum computers and how do they work?”. Wired.  https://www.wired.co.uk/article/quantum-computing-explained

  3. Aaronson, Scott (2008). “The Limits of Quantum” https://www.cs.virginia.edu/~robins/The_Limits_of_Quantum_Computers.pdf

  4. Greenberg, Andy (July 7, 2016). “Google Tests New Crypto to Fend Off Quantum Attacks”. Wired. https://www.wired.com/2016/07/google-tests-new-crypto-chrome-fend-off-quantum-attacks/

  5. Hartnett, Kevin (July 31, 2018).“Major Quantum Computing Advance Made Obsolete by Teenager”. Scientific American. https://www.quantamagazine.org/teenager-finds-classical-alternative-to-quantum-recommendation-algorithm-20180731/

  6. Greenemeier, Larry (May 30, 2018). “How Close Are We—Really—to Building a Quantum Computer?” https://www.scientificamerican.com/article/how-close-are-we-really-to-building-a-quantum-computer/

Comment

Share