How the algorithm tipped the balance in Ukraine


David Ignatius at The Washington Post: “Two Ukrainian military officers peer at a laptop computer operated by a Ukrainian technician using software provided by the American technology company Palantir. On the screen are detailed digital maps of the battlefield at Bakhmut in eastern Ukraine, overlaid with other targeting intelligence — most of it obtained from commercial satellites.

As we lean closer, we see can jagged trenches on the Bakhmut front, where Russian and Ukrainian forces are separated by a few hundred yards in one of the bloodiest battles of the war. A click of the computer mouse displays thermal images of Russian and Ukrainian artillery fire; another click shows a Russian tank marked with a “Z,” seen through a picket fence, an image uploaded by a Ukrainian spy on the ground.

If this were a working combat operations center, rather than a demonstration for a visiting journalist, the Ukrainian officers could use a targeting program to select a missile, artillery piece or armed drone to attack the Russian positions displayed on the screen. Then drones could confirm the strike, and a damage assessment would be fed back into the system.

This is the “wizard war” in the Ukraine conflict — a secret digital campaign that has never been reported before in detail — and it’s a big reason David is beating Goliath here. The Ukrainians are fusing their courageous fighting spirit with the most advanced intelligence and battle-management software ever seen in combat.

“Tenacity, will and harnessing the latest technology give the Ukrainians a decisive advantage,” Gen. Mark A. Milley, chairman of the Joint Chiefs of Staff, told me last week. “We are witnessing the ways wars will be fought, and won, for years to come.”

I think Milley is right about the transformational effect of technology on the Ukraine battlefield. And for me, here’s the bottom line: With these systems aiding brave Ukrainian troops, the Russians probably cannot win this war…(More)” See also Part 2.

We need data infrastructure as well as data sharing – conflicts of interest in video game research


Article by David Zendle & Heather Wardle: “Industry data sharing has the potential to revolutionise evidence on video gaming and mental health, as well as a host of other critical topics. However, collaborative data sharing agreements between academics and industry partners may also afford industry enormous power in steering the development of this evidence base. In this paper, we outline how nonfinancial conflicts of interest may emerge when industry share data with academics. We then go on to describe ways in which such conflicts may affect the quality of the evidence base. Finally, we suggest strategies for mitigating this impact and preserving research independence. We focus on the development of data infrastructure: technological, social, and educational architecture that facilitates unfettered and free access to the kinds of high-quality data that industry hold, but without industry involvement…(More)”.

Public sector innovation has a “first mile” problem


Article by Catarina Tully, and Giulio Quaggiotto: “Even if progress has been uneven, the palette of innovation approaches adopted by the public sector has considerably expanded in the last few years: from new sources of data to behavioural science, from foresight to user-centred design, from digital transformation to system thinking. And yet, the frustration of many innovation champions within the government is palpable. We are all familiar with innovation graveyards and, in our learning journeys, probably contributed to them in spite of all best intentions:

  • Dashboards that look very “smart” and are carefully tended to by few specialists but never used by their intended target audience: decision-makers.
  • Prototypes or experiments that were developed by an innovation unit and meant to be handed over to a line ministry or city department but never were.
  • Beautifully crafted scenarios and horizon scanning reports that last the length of a press conference or a ribbon-cutting event and are quickly put on the shelves after that.

The list could go on and on.

Innovation theatre is a well known malaise (paraphrasing Sean McDonald: “the use of [technology] interventions that make people feel as if a government—and, more often, a specific group of political leaders—is solving a problem, without it doing anything to actually solve that problem.”)

In the current climate, the pressure to “scale” quick-fixes in the face of multiple crises (as opposed to the hard work of addressing root causes, building trust, and structural transformations) is only increasing the appetite for performative theatre. Eventually, public intrapreneurs learn to use the theatre to their advantage: let the photo op with the technology gadget or the “futuristic” scenario take the centre stage so as to create goodwill with the powers that be, while you work quietly in the backstage to do the “right” thing…(More)”.

How to spot AI-generated text


Article by Melissa Heikkilä: “This sentence was written by an AI—or was it? OpenAI’s new chatbot, ChatGPT, presents us with a problem: How will we know whether what we read online is written by a human or a machine?

Since it was released in late November, ChatGPT has been used by over a million people. It has the AI community enthralled, and it is clear the internet is increasingly being flooded with AI-generated text. People are using it to come up with jokes, write children’s stories, and craft better emails. 

ChatGPT is OpenAI’s spin-off of its large language model GPT-3, which generates remarkably human-sounding answers to questions that it’s asked. The magic—and danger—of these large language models lies in the illusion of correctness. The sentences they produce look right—they use the right kinds of words in the correct order. But the AI doesn’t know what any of it means. These models work by predicting the most likely next word in a sentence. They haven’t a clue whether something is correct or false, and they confidently present information as true even when it is not. 

In an already polarized, politically fraught online world, these AI tools could further distort the information we consume. If they are rolled out into the real world in real products, the consequences could be devastating. 

We’re in desperate need of ways to differentiate between human- and AI-written text in order to counter potential misuses of the technology, says Irene Solaiman, policy director at AI startup Hugging Face, who used to be an AI researcher at OpenAI and studied AI output detection for the release of GPT-3’s predecessor GPT-2. 

New tools will also be crucial to enforcing bans on AI-generated text and code, like the one recently announced by Stack Overflow, a website where coders can ask for help. ChatGPT can confidently regurgitate answers to software problems, but it’s not foolproof. Getting code wrong can lead to buggy and broken software, which is expensive and potentially chaotic to fix…(More)”.

How AI That Powers Chatbots and Search Queries Could Discover New Drugs


Karen Hao at The Wall Street Journal: “In their search for new disease-fighting medicines, drug makers have long employed a laborious trial-and-error process to identify the right compounds. But what if artificial intelligence could predict the makeup of a new drug molecule the way Google figures out what you’re searching for, or email programs anticipate your replies—like “Got it, thanks”?

That’s the aim of a new approach that uses an AI technique known as natural language processing—​the same technology​ that enables OpenAI’s ChatGPT​ to ​generate human-like responses​—to analyze and synthesize proteins, which are the building blocks of life and of many drugs. The approach exploits the fact that biological codes have something in common with search queries and email texts: Both are represented by a series of letters.  

Proteins are made up of dozens to thousands of small chemical subunits known as amino acids, and scientists use special notation to document the sequences. With each amino acid corresponding to a single letter of the alphabet, proteins are represented as long, sentence-like combinations.

Natural language algorithms, which quickly analyze language and predict the next step in a conversation, can also be applied to this biological data to create protein-language models. The models encode what might be called the grammar of proteins—the rules that govern which amino acid combinations yield specific therapeutic properties—to predict the sequences of letters that could become the basis of new drug molecules. As a result, the time required for the early stages of drug discovery could shrink from years to months.

“Nature has provided us with tons of examples of proteins that have been designed exquisitely with a variety of functions,” says Ali Madani, founder of ProFluent Bio, a Berkeley, Calif.-based startup focused on language-based protein design. “We’re learning the blueprint from nature.”…(More)”.

Storytelling Will Save the Earth


Article by Bella Lack: “…The environmental crisis is one of overconsumption, carbon emissions, and corporate greed. But it’s also a crisis of miscommunication. For too long, hard data buried environmentalists in an echo-chamber, but in 2023, storytelling will finally enable a united global response to the environmental crisis. As this crisis worsens, we will stop communicating the climate crisis with facts and stats—instead we will use stories like Timothy’s.  

Unlike numbers or facts, stories can trigger an emotional response, harnessing the power of motivation, imagination, and personal values, which drive the most powerful and permanent forms of social change. For instance, in 2019, we all saw the images of Notre Dame cathedral erupting in flames. Three minutes after the fire began, images of the incident were being broadcast globally, eliciting an immediate response from world leaders. That same year, the Amazon forest also burned, spewing smoke that spread over 2,000 miles and burning over one and a half football fields of rain forest every minute of every day—it took three weeks for the mainstream media to report that story. Why did the burning of Notre Dame warrant such rapid responses globally, when the Amazon fires did not? Although it is just a beautiful assortment of limestone, lead, and wood, we attach personal significance to Notre Dame, because it has a story we know and can relate to. That is what propelled people to react to it, while the fact that the Amazon was on fire elicited nothing…(More)”.

Storytelling allows us to make sense of the world. 

The Risks of Empowering “Citizen Data Scientists”


Article by Reid Blackman and Tamara Sipes: “New tools are enabling organizations to invite and leverage non-data scientists — say, domain data experts, team members very familiar with the business processes, or heads of various business units — to propel their AI efforts. There are advantages to empowering these internal “citizen data scientists,” but also risks. Organizations considering implementing these tools should take five steps: 1) provide ongoing education, 2) provide visibility into similar use cases throughout the organization, 3) create an expert mentor program, 4) have all projects verified by AI experts, and 5) provide resources for inspiration outside your organization…(More)”.

A catalyst for community-wide action on sustainable development


Article by Communities around the world are increasingly recognizing that breaking down silos and leveraging shared resources and interdependencies across economic, social, and environmental issues can help accelerate progress on multiple issues simultaneously. As a framework for organizing local development priorities, the world’s 17 Sustainable Development Goals (SDGs) uniquely combine a need for broad technical expertise with an opportunity to synergize across domains—all while adhering to the principle of leaving no one behind. For local leaders attempting to tackle intersecting issues using the SDGs, one underpinning question is how to support new forms of collaboration to maximize impact and progress?

In early May, over 100 people across the East Central Florida (ECF) region in the U.S. participated in Partnership for the Goals: Creating a Resilient and Thriving Community,” a two-day multi-stakeholder convening spearheaded by a team of local leaders from the East Central Florida Regional Resilience Collaborative (ECFR2C), the Central Florida Foundation, the City of Orlando, Florida for Good, Orange County, and the University of Central Florida. The convening grew out of a multi-year resilience planning process that leveraged the SDGs as a framework for tackling local economic, social, and environmental priorities all at once.

To move from community-wide planning to community-wide action, the organizers experimented with a 17 Rooms process—a new approach to accelerating collaborative action for the SDGs pioneered by the Center for Sustainable Development at Brookings and The Rockefeller Foundation. We collaborated with the ECF local organizing team and, in the process, spotted a range of more broadly relevant insights that we describe here…(More)”.

Which Connections Really Help You Find a Job?


Article by Iavor Bojinov, Karthik Rajkumar, Guillaume Saint-Jacques, Erik Brynjolfsson, and Sinan Aral: “Whom should you connect with the next time you’re looking for a job? To answer this question, we analyzed data from multiple large-scale randomized experiments involving 20 million people to measure how different types of connections impact job mobility. Our results, published recently in Science Magazine, show that your strongest ties — namely your connections to immediate coworkers, close friends, and family — were actually the least helpful for finding new opportunities and securing a job. You’ll have better luck with your weak ties: the more infrequent, arm’s-length relationships with acquaintances.

To be more specific, the ties that are most helpful for finding new jobs tend to be moderately weak: They strike a balance between exposing you to new social circles and information and having enough familiarity and overlapping interests so that the information is useful. Our findings uncovered the relationship between the strength of the connection (as measured by the number of mutual connections prior to connecting) and the likelihood that a job seeker transitions to a new role within the organization of a connection.The observation that weak ties are more beneficial for finding a job is not new. Sociologist Mark Granovetter first laid out this idea in a seminal 1973 paper that described how a person’s network affects their job prospects. Since then, the theory, known as the “strength of weak ties,” has become one of the most influential in the social sciences — underpinning network theories of information diffusion, industry structure, and human cooperation….(More)”.

The Dangers of Systems Illiteracy


Review by Carol Dumaine: “In 1918, as the Great War was coming to an end after four bloody years of brutal conflict, an influenza pandemic began to ravage societies around the globe. While in Paris negotiating the terms of the peace agreement in the spring of 1919, evidence indicates that US president Woodrow Wilson was stricken with the flu. 

Wilson, who had been intransigent in insisting on just peace terms for the defeated nations (what he called “peace without victory”), underwent a profound change of mental state that his personal physician and closest advisors attributed to his illness. While sick, Wilson suddenly agreed to all the terms he had previously adamantly rejected and approved a treaty that made onerous demands of Germany. 

Wilson’s reversal left Germans embittered and his own advisors disillusioned. Historian John M. Barry, who recounts this episode in his book about the 1918 pandemic, The Great Influenza, observes that most historians agree “that the harshness toward Germany of the Paris peace treaty helped create the economic hardship, nationalistic reaction, and political chaos that fostered the rise of Hitler.” 

This anecdote is a vivid illustration of how a public health disaster can intersect with world affairs, potentially sowing the seeds for a future of war. Converging crises can leave societies with too little time to regroup, breaking down resilience and capacities for governance. Barry concludes from his research into the 1918 pandemic that to forestall this loss of authority—and perhaps to avoid future, unforeseen repercussions—government leaders should share the unvarnished facts and evolving knowledge of a situation. 

Society is ultimately based on trust; during the flu pandemic, “as trust broke down, people became alienated not only from those in authority, but from each other.” Barry continues, “Those in authority must retain the public’s trust. The way to do that is to distort nothing, to put the best face on nothing, to try to manipulate no one.”

Charles Weiss makes a similar argument in his new book, The Survival Nexus: Science, Technology, and World Affairs. Weiss contends that the preventable human and economic losses of the COVID-19 pandemic were the result of politicians avoiding harsh truths: “Political leaders suppressed evidence of virus spread, downplayed the importance of the epidemic and the need to observe measures to protect the health of the population, ignored the opinions of local experts, and publicized bogus ‘cures’—all to avoid economic damage and public panic, but equally importantly to consolidate political power and to show themselves as strong leaders who were firmly in control.” …(More)”.