The Futures - No. 03

By Quantumrun

May 02, 2023

TLDR: In this issue

We cover why we keep experiencing technology panic, the developments in gene editing, how the education system is treating ChatGPT, and geopolitical foresight on green energy economics.

The never-ending cycle of technology fear-mongering

Ever wondered why every time there is a disruptive technology, researchers, politicians, professors, and even your grandma suddenly become messengers of doom? A graduate of the University of Oxford for experimental psychology, Amy Orben, created a four-stage concept called the Sisyphean Cycle of Technological Anxiety to explain this phenomenon. Sisyphus is a character from Greek mythology who was fated to eternally push a boulder up a slope, only for it to roll back down, forcing him to repeat the process endlessly.

As illustrated by the chart below, the technology panic timeline is as follows:

A new technology appears → Politicians step in→ Researchers start focusing on popular topics to get funds→ After researchers publish their lengthy study findings, the media covers these results.

The same doomsday approach is being implemented on generative AI. Everyone is convinced it will displace millions of jobs, create a culture of lazy thinkers, and make disinformation and propaganda much easier. While these concerns do have merits, the technology is still relatively new, and no one can be entirely sure that it will not evolve to counter these trends. Yes, AI can create disinformation campaigns, but AI can also be used to detect them. The World Economic Forum predicts that by 2025, machines might replace around 85 million jobs; however, they could also generate 97 million new positions better suited to the evolving collaboration among humans, machines, and algorithms.

We need self-awareness in various situations — an understanding of how we, individually and collectively, respond adversely to new experiences. For example, what were we once afraid of but now embrace? What lessons did we gain from these experiences? By answering these questions, we can integrate that knowledge into our actions.

Wider implications of technology fear-mongering may include:

Increased distrust and anxiety towards technological advancements, potentially causing a reluctance to adopt new technologies.
Hindered economic growth and innovation by creating an environment where entrepreneurs, investors, and businesses are less likely to pursue new technological ventures due to perceived risks.
Politicians exploiting public fears for political gain, leading to restrictive policies, overregulation, or bans on specific technologies, which can stifle innovation.
A widening digital divide between different demographic groups. Younger generations, who are generally more tech-savvy, may have greater access to and understanding of new technologies, while older generations may be left behind.
Stagnation in technological advancements, resulting in a lack of breakthroughs and improvements in crucial areas like healthcare, transportation, and renewable energy.
The fear of job loss due to automation preventing the adoption of more efficient and environmentally friendly technologies, prolonging a dependence on traditional, less sustainable industries.

Future signals to watch

The factories of the future will be highly interconnected, utilizing a combination of technologies, such as artificial intelligence, data platforms, edge devices, cloud computing, robotics, and sensors.
Be ready to receive AI-generated spam in your inbox, and they might sound oddly convincing.
The increasing presence of AI in healthcare may lead to a rise in AI paternalism, which can overshadow patient experiences and clinical judgment.
ChatGPT may be establishing a wall of mistrust between clients and freelancers.
Psychedelic medicine might be closer than ever as the US Food and Drug Administration may soon approve MDMA treatments.
London-based think tank Ember predicts that for the first time, greenhouse gas emissions from the power sector, the world's largest emissions contributor, will decrease in 2023.
China is exporting its surveillance technology to Iran, where women are punished for not wearing a headscarf.

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Is gene editing becoming safer?

Credit: MIT Technology Review / Artist: Daniel Savage

CRISPR-Cas9 is a popular gene-editing tool for finding new drugs and medical treatments. However, some research groups found that this tool can cause unexpected gene changes that can potentially trigger cancer. Scientists at Recursion Pharmaceuticals dug deeper into the problem and discovered that a tiny portion of cells experience "proximity bias." Before editing, CRISPR-Cas9 accidentally creates a double-stranded DNA break that can harm genes close to the target gene on the same chromosome arm. Afterward, the body incorrectly fixes the damage, leading to proximity bias.

Because of the great potential of genetic therapies, scientists are constantly looking for ways to make CRISPR-Cas9 safer. Researchers at Kyushu University and Nagoya University School of Medicine in Japan have developed an improved genome-editing method that significantly lowers the rate of mutations, a fine-tuning system they called “safeguard gRNA.” The team is currently developing a start-up business plan to expand the reach of their new genome editing platform.

One of the most widely debated potential use cases of more accurate gene editing is the early correction in human embryos. However, initial studies in the field showed that the technology is still too unpredictable. Scientists at Oregon Health & Science University discovered that fixing disease-causing mutations in early human embryos through gene editing may also result in unexpected and possibly harmful genome alterations. The results provide a new caution for researchers considering using genetically edited embryos to initiate pregnancies. The quest for the perfect human seems to be a long way off.

Wider implications of safer gene editing tools may include:

New markets for gene editing services, diagnostics, and therapies, resulting in shifts in healthcare spending and distribution of resources.
National and international regulations being established to govern the use of gene editing technologies.
Further innovation in agriculture, biotechnology, and pharmaceuticals, resulting in the development of novel products and industries that rely on gene editing tools.
Increased demand for skilled professionals in biotechnology, genetics, and related fields. This trend can lead to new educational programs and training opportunities to prepare the workforce for these industries.
Personalized medicine, where therapies are tailored to an individual's genetic makeup, resulting in a more effective and efficient healthcare system.
Moral and ethical implications of manipulating the human genome. Society will need to grapple with the balance between the potential benefits of gene editing and the possible risks associated with altering our genetic makeup.

Trending research reports from the world wide web

Recruitment platform Starred released its Hiring Manager Satisfaction Benchmark Report, outlining the characteristics of the best- and worst-performing teams.
The World Economic Forum’s 2023 Global Risks Report investigates some of the gravest dangers we could encounter in the coming 10 years.
In an unstable Q1 2023, global venture capital funding experienced a significant drop across all stages, even with huge OpenAI and Stripe transactions. Startups might need to tighten their belts.

The education system doesn’t know how to deal with ChatGPT

Credit: Science News Explores / Artist: Glenn Harvey

The cheating industry is notoriously known for hiring freelancers from emerging economies to write essays and homework for students in developed countries. Kenya is one of the most significant hubs in the sector, where an average freelance writer can earn between USD $900 to $1,200 every month for what they call “academic writing.” However, ChatGPT and other AI content services are taking over these jobs, with some freelancers reporting their income has dropped to USD $500–$800 monthly.

In a survey of 100 educators and over 1,000 students by Study.com, it was discovered that nearly 90 percent of students used ChatGPT for homework, 53 percent used it to write an essay, and 48 percent utilized it for at-home tests. With these numbers, offshoring content services may no longer be as needed (or cost-effective). Nonetheless, the cheating industry might still have an ace: The schools’ increasing bans against AI-assisted tools. Some academic writing providers in Kenya agree that ChatGPT can improve the quality and volume of their output.

Education systems are still at a loss as to how to integrate AI into the classroom but also teach students to use it responsibly. Some institutions have taken a proactive approach and banned ChatGPT entirely. In January 2023, New York City became the first US school district to ban ChatGPT in its public schools. The Los Angeles Unified School District, which is the second biggest, also quickly took action to restrict access to OpenAI's website from their school networks. Similarly, Baltimore in Maryland, Oakland Unified in California, and Seattle Public Schools have implemented the same restrictions. However, some universities, like Princeton and Cornell, are more welcoming toward the tool, acknowledging its increasing influence in the future of work.

Wider implications of ChatGPT in education may include:

The development of new technologies that incorporate artificial intelligence into the classroom, including personalized learning programs, virtual tutors, and automated grading systems.
Students with disabilities or those living in remote areas having better access to personalized educational resources through online platforms incorporating chatGPT.
Reduced need for traditional classroom infrastructure and materials, which could lead to cost savings for both educational institutions and students.
New policy and regulatory challenges, including questions around data privacy, ownership, and accountability in developing and deploying AI technologies in education.
Increasing debates on how AI should be regulated and integrated into formal education.

Outside curiosities

Days after the music world was rocked by an AI-generated song that cloned the voices of Drake and The Weeknd, musician Grimes invited fans to use AI-generated versions of her voice to write any song. The revenue split? 50-50.
Can’t get enough of eerily good AI-generated music? The world’s first AI music streaming platform, Apollo, is here to serve.
Radar satellites discovered an astounding 19,000 undersea volcanoes. This new seamount map could give valuable information on plate tectonics.
TikTok videos on how to bypass the ignition of Kia and Hyundai cars went viral. Hyundai is blaming them for the rise in car thefts across US cities.

Geopolitical foresight: The challenges of green energy economics

The Paris Agreement, the growth of ethically minded investors, the rise of environmental, social, and governance (ESG) regulations, and the attempts to break free from Russian oil are all putting pressure on governments to aggressively invest in green energy. However, everyone is finding out that it’s uphill work. While the long-term costs of green energy may be comparable to fossil fuels, financing the upfront construction costs is difficult.

The COVID-19 pandemic has slowed down investments in green energy infrastructure. Wind turbine manufacturer Vestas reported delays in acquiring parts and alterations in work processes led to an additional USD $10.8 million in expenses during the first quarter of 2021, resulting in a USD $88 million loss. Moreover, there is the issue of inelasticity in energy costs. As demand for specific resources increases during a green transition, the prices of materials like copper, aluminum, and lithium will also rise. Copper production, in particular, can face a shortage due to the material also being heavily used in electric vehicles.

The primary strategy in this situation is not to abandon green energy projects but to deploy them where the geography and capacity align. This technique means implementing solar in sunny regions and wind power in windy areas. An example is Australia, which is poised to become a renewable energy superpower. There is also a need for better technologies, particularly in transmission, to efficiently deliver electricity from where it's produced to where it's needed. Achieving this requires multiple acts of governments to fund research and facilitate power transmission across different jurisdictions and power grids.

Wider implications of addressing green energy economics may include:

Governments increasingly reassessing their green energy investments to optimize where renewable energy infrastructure is built domestically.
Increased regional infrastructure collaboration where countries may co-invest in cross-national energy transmission grids to trade energy between southern countries capable of generating significant solar energy and those that can generate significant wind energy (among other examples).
A more equitable distribution of resources, as renewable energy technologies can be implemented in both urban and rural areas and developing countries.
Greater energy independence and security, reducing regional dependence on foreign oil and creating a sense of community self-sufficiency.
Economic growth and job creation in new industries such as solar, wind, and energy storage. Investments in renewable energy infrastructure can stimulate local economies, create new business opportunities, and promote sustainable economic development.
Innovation in renewable energy technologies, leading to energy efficiency, storage, and distribution advancements.