Carbon capture, utilization, and storage: Technologies and costs in the U.S. context
The Biden administration has set a goal of reaching net zero economy-wide greenhouse gas emissions by 2050.
Research
Spaceship or Stewardship: Imaginaries of Sustainability in the Information Age
This paper contrasts two approaches to implementing the notoriously ambiguous ideal of sustainability: one driven by the centralized, managerial metaphor of Spaceship Earth, and the other by a notion
Knowledge for a just climate
First, science generated without regard to questions about whose purposes it serves is not likely to persuade those who feel that their needs and interests were not heeded by the knowledge-makers.
Transnational families and technology: trends, impacts and futures
The digital age presents a complex array of opportunities and threats for transnational families.
Probability Paths and the Structure of Predictions over Time
In settings ranging from weather forecasts to political prognostications to financial projections, probability estimates of future binary outcomes often evolve over time.
The Great Tech Rivalry: China vs the U.S.
To mark the arrival of the 21st century, in 1999 the National Academies of Science, Engineering, and Medicine offered an Olympian preview of the decades ahead.
New urban challenges: Shared spaces in smart places – Overview and positioning
Modern cities face many new challenges as a result of the ‘digital age’, in particular the uncertain promise of high urban benefits from the widespread use of communication technology in a smart city
Confronting Cyber Risk: An Embedded Endurance Strategy for Cybersecurity
An adaptive cyber risk management guide from MIT scientist and Johns Hopkins professor Gregory Falco and "Cyber Czar" Eric Rosenbach Cyberattacks continue to grow in number, intensity, and sophistica
Mythmakers in the Market for Perfection
Henry Kissinger, Benjamin Franklin, Steve Jobs, Albert Einstein, Leonardo da Vinci: Giants in their fields and times, these men also have the distinction of having received full biographical treatment
Breaking Taboos in Fair Machine Learning: An Experimental Study
Many scholars, engineers, and policymakers believe that algorithmic fairness requires disregarding information about certain characteristics of individuals, such as their race or gender.
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