#data-driven outcome

[corporateintel]

Why We Focus

There’s a theme running through our workplace this year. It’s as simple as it is profound. It’s not revolutionary; it’s more of a reminder. It’s all about focus. Focus matters. Focus works. Focus wins. The “what” and “how” of focus are somewhat obvious. We need to set clear priorities, narrow our agenda to initiatives that significantly elevate performance, add resources to projects that will…

[modernmarketingmethods]

Not Just Advice: Global Consulting Services That Deliver Measurable Results

In a world where disruption is constant and competition is intense, business leaders are seeking more than just good advice. They want measurable outcomes, scalable systems, and strategies that drive growth and resilience. That’s why global consulting services have evolved from being traditional advice-givers to results-driven partners who empower organizations to achieve real, trackable improvements.

Today’s consulting and advisory services offer more than theoretical frameworks or cookie-cutter recommendations. They deliver tangible performance gains, process efficiencies, innovation roadmaps, and financial impact. The best consulting firms work hand-in-hand with clients, ensuring that strategies are implemented effectively and aligned with measurable business goals.

If you’re skeptical about whether consulting can make a real difference in your company’s success, here’s what separates modern global consulting services from generic advice and why their results speak for themselves.

A Focus on Strategic Execution, Not Just Planning

One of the most common complaints about consultants is that they offer grand strategies without supporting execution. That’s no longer the case with today’s consulting and advisory services. They are deeply involved in implementation, ensuring that solutions don’t just look good on paper but actually work in the field.

Global consulting services support clients from start to finish, from initial assessment and roadmapping to employee training, performance monitoring, and continuous optimization. Their role is to transfer knowledge, tools, and capabilities that stay with the organization long after the engagement ends.

Execution support means fewer delays, better adoption of new processes, and quicker realization of results.

Aligning Recommendations with Measurable KPIs

Modern consulting isn’t about vague ideas. It’s about quantifiable improvement. Consulting and advisory services work with clients to set clear key performance indicators (KPIs) and success benchmarks. These could include cost savings, increased revenue, reduced churn, improved productivity, higher customer satisfaction, or stronger ROI.

The focus is on building dashboards and reporting structures that allow business leaders to track progress in real time. This transparency builds trust and ensures accountability on both sides of the engagement.

When global consulting services deliver a 20% reduction in operational costs or a 15% increase in supply chain efficiency, it’s no longer a question of whether the investment was worth it — the results speak for themselves.

Sector-Specific Expertise That Drives Targeted Results

Not all businesses face the same challenges. What works for a tech startup may not apply to a healthcare provider or a manufacturing firm. That’s why specialized consulting and advisory services bring sector-specific experience to each engagement.

They understand industry regulations, market conditions, operational dynamics, and technology trends that are unique to your field. This allows for tailored solutions that are relevant, realistic, and results-driven.

Global consulting services often bring best practices from around the world, drawing on global case studies and proven success models to give your business a competitive edge. Whether it's navigating healthcare compliance, implementing manufacturing automation, or scaling digital platforms in retail, consultants can deliver transformation at speed and scale.

Data-Driven Insights and Continuous Optimization

Consulting today is built on a strong foundation of data and analytics. Decisions are no longer based on gut feelings or outdated assumptions. Consulting and advisory services use real-time data, predictive modeling, and advanced analytics to guide recommendations.

This data-driven approach ensures that your strategies are grounded in reality and continuously refined. By monitoring performance metrics and customer feedback, consultants help businesses stay agile and proactive.

Global consulting services also help companies adopt tools that improve internal analytics capabilities. From cloud-based dashboards to AI-driven performance monitoring systems, these tools allow organizations to make smarter, faster decisions long after the consultants are gone.

Real Organizational Change, Not Just Temporary Fixes

Many consulting engagements fail because they don’t address internal challenges like team resistance, misalignment, or lack of leadership buy-in. This is why modern consulting and advisory services focus heavily on change management and organizational development.

They offer leadership coaching, cultural transformation programs, and internal communication strategies that help embed new ways of working. This ensures that changes stick and continue to produce results over time.

Global consulting services also work to build internal capabilities so that your team can sustain the progress. Rather than creating dependency, they empower you to drive future improvements on your own.

Long-Term Value and Sustainable Growth

Businesses no longer view consulting as a short-term patch. They see it as a strategic partnership for long-term value. Consulting and advisory services now focus on helping organizations build sustainable models that deliver ongoing returns.

Whether it's developing a three-year digital transformation plan, restructuring a global supply chain, or creating a talent retention strategy, the emphasis is on long-term value creation.

Global consulting services are particularly valuable for businesses looking to expand into new markets or manage complex global operations. They provide the knowledge, tools, and networks needed to grow confidently and sustainably.

Final Thoughts: More Than Just a Smart Choice

The misconception that consultants only offer advice is outdated. Today’s global consulting services are deeply integrated into how successful companies grow, adapt, and outperform competitors.

From improving efficiency to accelerating innovation, from reducing risk to increasing profits, the best consulting and advisory services deliver clear, measurable business outcomes.

If your organization is serious about growth, strategy, and transformation, it’s time to stop viewing consulting as optional. It’s time to see it for what it is: a powerful driver of results.

[projectchampionz]

STRATEGIES FOR EFFECTIVE PROJECT MANAGEMENT IN COMPLEX HEALTHCARE ENVIRONMENTS

STRATEGIES FOR EFFECTIVE PROJECT MANAGEMENT IN COMPLEX HEALTHCARE ENVIRONMENTS 1.1 Introduction Project management is critical in healthcare environments, where the complexity of operations, regulations, and patient care makes effective oversight essential. Healthcare projects often involve multiple stakeholders, extensive resources, and high-stakes outcomes, necessitating precise coordination…

[marketxcel]

Benefits of Using an Online B2B Panel for Surveys

This blog will explore the advantages of using an online B2B panel for surveys and how it can empower companies with valuable data for better decision-making.

[covid-safer-hotties]

Also preserved on our archive

By Bill Shaw

A new study in eClinicalMedicine has found that healthy volunteers infected with SARS-CoV-2 had measurably worse cognitive function for up to a year after infection when compared to uninfected controls. Significantly, infected controls did not report any symptoms related to these cognitive deficits, indicating that they were unaware of them. The net effect is that potentially billions of people worldwide with a history of COVID-19, but no symptoms of long COVID, could have persistent cognitive issues without knowing it.

The study’s lead author, Adam Hampshire, professor of cognitive and computational neuroscience at King's College London, said:

"It … is the first study to apply detailed and sensitive assessments of cognitive performance from pre to post infection under controlled conditions. In this respect, the study provides unique insights into the changes that occurred in cognitive and memory function amongst those who had mild COVID-19 illness early in the pandemic."

This news comes as pandemic mitigation measures have all but been abandoned by governments across the globe. Public health practice has been decimated to the point where even surveillance data on SARS-CoV-2 infections and resulting hospitalizations, deaths, and other outcomes are barely collected let alone published.

The data that are available indicate, per the most recent modeling from the Pandemic Mitigation Collaborative (PMC) on September 23, that since the beginning of August there have been over 1 million infections per day in the US alone. This level of transmission is expected to persist through the remainder of September and all of October. For the months of August through October, these levels of transmission are the highest of the entire pandemic

The study on cognitive deficits has been shared widely across social media, with scientists and anti-COVID advocates drawing out its dire implications.

Australian researcher and head of the Burnet Institute, Dr. Brendan Crabb, who has previously advocated for a global elimination strategy to stop the pandemic, wrote:

"Ethical issues aside, this is a powerful addition to an already strong dataset on Covid-driven brain damage affecting cognition & memory. Given new (re)infections remain common, this work… should influence a re-think on current prevention/treatment approaches."

The study enrolled 36 healthy volunteers. These individuals had no history of prior SARS-CoV-2 infection, no risk factors for severe COVID-19, and no history of SARS-CoV-2 vaccination. The researchers determined whether the volunteers were seronegative prior to inoculation, meaning that they had no detectable antibodies to SARS-CoV-2. If such antibodies were present, it would indicate past infection or vaccination.

These procedures resulted in a total of data from 34 volunteers being included for analysis. Two volunteers were excluded from analysis because they had seroconverted to positive for SARS-CoV-2 antibodies between the time of screening and inoculation. Notably, these two volunteers participated in all subsequent study activities, enabling a sensitivity analysis of the results that included them.

The researchers inoculated all 36 volunteers with SARS-CoV-2 virus in the nose and then quarantined them for at least 14 days. Volunteers only returned home once they had two consecutive daily nasal and throat swabs that were negative for virus. Thus, those volunteers who had an infection after inoculation spent the duration of their infection in quarantine. This quarantine was required by ethical study protocols, in order that the study itself not increase community transmission of the virus.

The researchers collected data on the volunteers daily during quarantine and at follow-up visits at 30, 90, 180, 270, and 360 days post-inoculation. The assessments included body temperature, viral loads from throat and nasal swabs, surveys on symptoms, and computer-based cognitive tests on 11 major cognitive tasks. The cognitive testing varied the particular exercise for each of the 11 tasks to avoid learning and memorization of solutions in subsequent sessions. Nevertheless, some tasks were more prone to learning so the researchers also studied the effect of infection on “learning” vs. “non-learning” tasks.

Of the 36 inoculated volunteers, 18 became infected and developed COVID-19 and 16 did not. The two groups did not differ significantly in key demographics. No volunteers required hospitalization or supplemental oxygen during the study. Every volunteer completed all five follow-up visits. 15 volunteers acquired a non-COVID upper respiratory tract infection in their community between the end of quarantine and the fifth visit at day 360.

The researchers found that the infected group had significantly lower average “baseline-corrected global composite cognitive score” (bcGCCS) than the uninfected group at all follow-up intervals. At baseline, the two groups did not differ significantly. The difference between the two groups did not significantly vary by time, meaning that the infected group’s bcGCCS did not improve during the nearly year-long study.

Because the bcGCCS was a composite based on individual scores for the 11 cognitive tasks, the researchers also looked at which tasks in particular were impacted. They found that the most affected task was related to immediate object memory, in particular, recall of the spatial orientation of the object. There was no difference in picking the correct object itself, just its spatial orientation. This means that infected individuals had a hard time choosing the correct spatial orientation of the object they had just seen, for example, erroneously picking a mirror image of the object they had just seen.

The results were not different based on sex, learning vs. non-learning tasks, or whether individuals received remdesivir or had community-acquired upper respiratory infections.

Because the investigators controlled for so many factors including the strain of SARS-CoV-2, timing of infection, quarantine, and lack of prior infection and vaccination, the study provides high confidence that SARS-CoV-2 infection was responsible for the cognitive defects. The control of the timing of infection also enabled clarification of whether and when cognitive deficits occurred and improved. The differences between the groups were apparent by day 14 of quarantine and as noted previously, the deficits in the infected group did not improve let alone resolve.

The symptom surveys did not differ between the two groups. None of the volunteers, infected or uninfected, reported subjective cognitive issues or symptoms. Thus the infected volunteers with measurable cognitive deficits at one year post-infection were not aware of these deficits.

The study reaffirms prior research into persistent cognitive deficits and brain damage associated with COVID-19, including other studies which have found deficits among patients without symptomatic long COVID. Building upon this prior research, the latest study indicates that basically every single unvaccinated individual with a history of acute COVID-19 is at risk for persistent, measurable cognitive deficits.

Given that other studies have shown that vaccination reduces one’s risk of long COVID by roughly half, similar measurable cognitive deficits are likely prevalent among vaccinated people who suffer “breakthrough” infection, albeit likely at reduced rates of decline.

The study raises the urgent questions about the level of protection provided by vaccination, whether strains since the original “wild type” SARS-CoV-2 strain have similar effects on cognition, and what is the impact of these cognitive deficits on people’s performance at home, work, and school.

The study also adds to the large body of damning evidence that the ruling class’ “forever COVID” policy is of immense criminal proportions. Enabling a dangerous, mind-damaging virus to circulate among humanity worldwide represents a scale of inhumanity and dereliction of duty that is practically unfathomable. The malignity of this intentional policy is underscored by the current situation where the U.S. alone has had over 1 million new infections per day since August, with levels not projected to drop below 1 million until November.

The working class must deepen the struggle to replace the capitalist system that prioritizes profit over lives with a world socialist society that places human needs first.

Study Link: www.thelancet.com/journals/eclinm/article/PIIS2589-5370%2824%2900421-8/fulltext

[mariacallous]

A lawsuit filed Wednesday against Meta argues that US law requires the company to let people use unofficial add-ons to gain more control over their social feeds.

It’s the latest in a series of disputes in which the company has tussled with researchers and developers over tools that give users extra privacy options or that collect research data. It could clear the way for researchers to release add-ons that aid research into how the algorithms on social platforms affect their users, and it could give people more control over the algorithms that shape their lives.

The suit was filed by the Knight First Amendment Institute at Columbia University on behalf of researcher Ethan Zuckerman, an associate professor at the University of Massachusetts—Amherst. It attempts to take a federal law that has generally shielded social networks and use it as a tool forcing transparency.

Section 230 of the Communications Decency Act is best known for allowing social media companies to evade legal liability for content on their platforms. Zuckerman’s suit argues that one of its subsections gives users the right to control how they access the internet, and the tools they use to do so.

“Section 230 (c) (2) (b) is quite explicit about libraries, parents, and others having the ability to control obscene or other unwanted content on the internet,” says Zuckerman. “I actually think that anticipates having control over a social network like Facebook, having this ability to sort of say, ‘We want to be able to opt out of the algorithm.’”

Zuckerman’s suit is aimed at preventing Facebook from blocking a new browser extension for Facebook that he is working on called Unfollow Everything 2.0. It would allow users to easily “unfollow” friends, groups, and pages on the service, meaning that updates from them no longer appear in the user’s newsfeed.

Zuckerman says that this would provide users the power to tune or effectively disable Facebook’s engagement-driven feed. Users can technically do this without the tool, but only by unfollowing each friend, group, and page individually.

There’s good reason to think Meta might make changes to Facebook to block Zuckerman’s tool after it is released. He says he won’t launch it without a ruling on his suit. In 2020, the company argued that the browser Friendly, which had let users search and reorder their Facebook news feeds as well as block ads and trackers, violated its terms of service and the Computer Fraud and Abuse Act. In 2021, Meta permanently banned Louis Barclay, a British developer who had created a tool called Unfollow Everything, which Zuckerman’s add-on is named after.

“I still remember the feeling of unfollowing everything for the first time. It was near-miraculous. I had lost nothing, since I could still see my favorite friends and groups by going to them directly,” Barclay wrote for Slate at the time. “But I had gained a staggering amount of control. I was no longer tempted to scroll down an infinite feed of content. The time I spent on Facebook decreased dramatically.”

The same year, Meta kicked off from its platform some New York University researchers who had created a tool that monitored the political ads people saw on Facebook. Zuckerman is adding a feature to Unfollow Everything 2.0 that allows people to donate data from their use of the tool to his research project. He hopes to use the data to investigate whether users of his add-on who cleanse their feeds end up, like Barclay, using Facebook less.

Sophia Cope, staff attorney at the Electronic Frontier Foundation, a digital rights group, says that the core parts of Section 230 related to platforms’ liability for content posted by users have been clarified through potentially thousands of cases. But few have specifically dealt with the part of the law Zuckerman’s suit seeks to leverage.

“There isn’t that much case law on that section of the law, so it will be interesting to see how a judge breaks it down,” says Cope. Zuckerman is a member of the EFF’s board of advisers.

John Morris, a principal at the Internet Society, a nonprofit that promotes open development of the internet, says that, to his knowledge, Zuckerman’s strategy “hasn’t been used before, in terms of using Section 230 to grant affirmative rights to users,” noting that a judge would likely take that claim seriously.

Meta has previously suggested that allowing add-ons that modify how people use its services raises security and privacy concerns. But Daphne Keller, director of the Program on Platform Regulation at Stanford's Cyber Policy Center, says that Zuckerman’s tool may be able to fairly push back on such an accusation.“The main problem with tools that give users more control over content moderation on existing platforms often has to do with privacy,” she says. “But if all this does is unfollow specified accounts, I would not expect that problem to arise here."

Even if a tool like Unfollow Everything 2.0 didn’t compromise users’ privacy, Meta might still be able to argue that it violates the company’s terms of service, as it did in Barclay’s case.

“Given Meta’s history, I could see why he would want a preemptive judgment,” says Cope. “He’d be immunized against any civil claim brought against him by Meta.”

And though Zuckerman says he would not be surprised if it takes years for his case to wind its way through the courts, he believes it’s important. “This feels like a particularly compelling case to do at a moment where people are really concerned about the power of algorithms,” he says.

[drdemonprince]

By now, a majority of Autism researchers and clinicians are aware that the existing assessments for Autism are profoundly flawed. 

They know the standard evaluation of Autism is sexist, with assessors excluding women for reasons like wearing makeup, having a boyfriend, being superficially polite, or not being fixated on suitably ‘masculine’ topics like ancient Roman history or barometric pressure. 

They know Autism evaluations are racist, deeming Black Autistics “oppositionally defiant” or even “borderline” rather than acknowledging any social alienation or sensory pain they’re experiencing, and believing they must be overstating the difficulty they face in moving through the world.

And they certainly know that conventional Autism measures weren’t designed with adult Autistics in mind. Many of us are still asked to make up stories based on paintings of frogs in a toddler’s picture book, when we sit down for assessments at age 20, or 30, or 45 — because all the evaluation methods were written for young kids. 

The data has already proven the far-reaching consequences of using such shoddy measures of Autism. People of color, gender minorities, older adults, and women are diagnosed at later ages, and also go undiagnosed at massive rates. 

A growing population of scientists are admittedly interested in fostering a new literature of what they call “patient-driven” Autism research, but they never stop thinking of us as mere patients, the passive receivers of care rather than the leaders of communities and political movements who are the ought to be the primary authors of the studies about us, and the sole determinants of what our desired outcomes should be. Even when they observe that their work could benefit from a greater Autistic perspective, researchers do so from closed rooms, filled with other professionals who are largely not Autistic, wondering amongst themselves what it is that we want instead of learning to quiet their voices and follow our lead. 

Though many basically well-intentioned Autism researchers believe that Autism assessments need reform, what neurodiversity really needs is to abandon the diagnostic process altogether. If Autism is a benign, neutral, naturally occurring form of human difference that requires acceptance rather than a cure, then there’s no need to diagnose it as if it were a sickness. And if hundreds of thousands of Autistic women, people of color, queer people, and older people have been able to give a voice to ourselves and find one another without having ever been given a label by a professional, then improved professional labeling is not what we need. 

Autistic self-realization is the future of Autism assessment. We hold the collective wisdom, organizing ability, insight, and political power to define who we are. No authority figure should have to sign off on our identities. 

Because psychiatrists fail to diagnose such a large percentage of the Autistic population, many Autism researchers now accept self-identified Autistic adults within their subject pool. Within the peer-reviewed journal Autism in Adulthood, self-realized Autistics often make up the bulk of the participant sample, and they have repeatedly been found to be indistinguishable from their formally diagnosed peers. 

A growing body of research now also considers the presence of Autism-spectrum traits as qualifying for inclusion in many Autism studies. The data makes it quite obvious that Autistic people exist within all human groups, spread all throughout the world, and that a great many people have experiences in common with us who have not been formally diagnosed. This itself reveals that a formal diagnosis is hardly necessary, and that a psychiatric paradigm of accepting self-identification is inevitable. The researchers are increasingly already doing it.

You can read the full essay for free (or have it narrated to you!) at this link.

[reasonsforhope]

Determined to use her skills to fight inequality, South African computer scientist Raesetje Sefala set to work to build algorithms flagging poverty hotspots - developing datasets she hopes will help target aid, new housing, or clinics.

From crop analysis to medical diagnostics, artificial intelligence (AI) is already used in essential tasks worldwide, but Sefala and a growing number of fellow African developers are pioneering it to tackle their continent's particular challenges.

Local knowledge is vital for designing AI-driven solutions that work, Sefala said.

"If you don't have people with diverse experiences doing the research, it's easy to interpret the data in ways that will marginalise others," the 26-year old said from her home in Johannesburg.

Africa is the world's youngest and fastest-growing continent, and tech experts say young, home-grown AI developers have a vital role to play in designing applications to address local problems.

"For Africa to get out of poverty, it will take innovation and this can be revolutionary, because it's Africans doing things for Africa on their own," said Cina Lawson, Togo's minister of digital economy and transformation.

"We need to use cutting-edge solutions to our problems, because you don't solve problems in 2022 using methods of 20 years ago," Lawson told the Thomson Reuters Foundation in a video interview from the West African country.

Digital rights groups warn about AI's use in surveillance and the risk of discrimination, but Sefala said it can also be used to "serve the people behind the data points". ...

'Delivering Health'

As COVID-19 spread around the world in early 2020, government officials in Togo realized urgent action was needed to support informal workers who account for about 80% of the country's workforce, Lawson said.

"If you decide that everybody stays home, it means that this particular person isn't going to eat that day, it's as simple as that," she said.

In 10 days, the government built a mobile payment platform - called Novissi - to distribute cash to the vulnerable.

The government paired up with Innovations for Poverty Action (IPA) think tank and the University of California, Berkeley, to build a poverty map of Togo using satellite imagery.

Using algorithms with the support of GiveDirectly, a nonprofit that uses AI to distribute cash transfers, the recipients earning less than $1.25 per day and living in the poorest districts were identified for a direct cash transfer.

"We texted them saying if you need financial help, please register," Lawson said, adding that beneficiaries' consent and data privacy had been prioritized.

The entire program reached 920,000 beneficiaries in need.

"Machine learning has the advantage of reaching so many people in a very short time and delivering help when people need it most," said Caroline Teti, a Kenya-based GiveDirectly director.

'Zero Representation'

Aiming to boost discussion about AI in Africa, computer scientists Benjamin Rosman and Ulrich Paquet co-founded the Deep Learning Indaba - a week-long gathering that started in South Africa - together with other colleagues in 2017.

"You used to get to the top AI conferences and there was zero representation from Africa, both in terms of papers and people, so we're all about finding cost effective ways to build a community," Paquet said in a video call.

In 2019, 27 smaller Indabas - called IndabaX - were rolled out across the continent, with some events hosting as many as 300 participants.

One of these offshoots was IndabaX Uganda, where founder Bruno Ssekiwere said participants shared information on using AI for social issues such as improving agriculture and treating malaria.

Another outcome from the South African Indaba was Masakhane - an organization that uses open-source, machine learning to translate African languages not typically found in online programs such as Google Translate.

On their site, the founders speak about the South African philosophy of "Ubuntu" - a term generally meaning "humanity" - as part of their organization's values.

"This philosophy calls for collaboration and participation and community," reads their site, a philosophy that Ssekiwere, Paquet, and Rosman said has now become the driving value for AI research in Africa.

Inclusion

Now that Sefala has built a dataset of South Africa's suburbs and townships, she plans to collaborate with domain experts and communities to refine it, deepen inequality research and improve the algorithms.

"Making datasets easily available opens the door for new mechanisms and techniques for policy-making around desegregation, housing, and access to economic opportunity," she said.

African AI leaders say building more complete datasets will also help tackle biases baked into algorithms.

"Imagine rolling out Novissi in Benin, Burkina Faso, Ghana, Ivory Coast ... then the algorithm will be trained with understanding poverty in West Africa," Lawson said.

"If there are ever ways to fight bias in tech, it's by increasing diverse datasets ... we need to contribute more," she said.

But contributing more will require increased funding for African projects and wider access to computer science education and technology in general, Sefala said.

Despite such obstacles, Lawson said "technology will be Africa's savior".

"Let's use what is cutting edge and apply it straight away or as a continent we will never get out of poverty," she said. "It's really as simple as that."

-via Good Good Good, February 16, 2022

[tanadrin]

Trump seems like clear evidence candidates matter. He's the only thing going for the Republicans, he's taken the whole party down the road to fascism on the strength of his narcissism, he has an honest-to-god personality cult! And he's going to win the election because he seems "strong," and that's all American voters care about.

he mattered more in 2016, when that shift was primarily happening--but the tea party prefigured him, and iirc he wasn't even a candidate yet when the Onion ran that story about how the next Republican nominee was going to be just a white-hot sphere of rage. which is just to say that trump might have championed that shift, but he didn't cause it.

but, to be clear, this is just a hypothesis i think is worth batting about. i do think candidates matter, though sometimes it's hard to make direct data-driven apples-to-apples comparisons. like, for all the talk of harris's advantages over biden (and i think she definitely has real advantages!) she still just polls about within the MoE ahead of him.

but you're operating under some larger assumptions here that i think are worth rebutting for the sake of clarity of thought. for one, "american voters" do not prefer trump. they have in fact preferred Not Trump by distinct majorities in the last two elections! clearly lots of voters do *not* respond to his alleged "strength." two, according to the polls--and every other available line of evidence--this election will be very close. the idea that a trump win is a certainty at this point is simply absurd.

(and if trump does win, that will not make people expressing absolute certainty now that he would win correct. if i say "the next flip of this coin is absolutely 100% guaranteed to be heads," and it does turn up heads, i was still wrong about the probability, even if i was by chance correct about the outcome.)

[mr-entj]

Mr-entj, you always say to start from the problems we want to solve. But how exactly can we find out what those are and how good we are at doing that?

Related answer:

Career and impact

Look around everywhere and see what catches your interest. Here are a few places to start and questions to ask:

Your immediate environment. Look around you—at your situation, family, neighborhood, socioeconomic class, ethnic group, town, city, and country. What issues are affecting them? What conditions are you living in? How are you treated?

For example, a former classmate of mine, whose family was deeply impacted by the Korean War, went on to study at Harvard and earn her PhD at Oxford. Today, she’s a recognized expert on North Korean human rights issues, publishing and speaking on the topic worldwide (currently a guest lecturer at Oxford's Blavatnik School of Government).

Within society. Check the news, social media, and entertainment channels. What themes keep surfacing? What news headlines are most fascinating or disturbing?

For example, I have a friend who was deeply troubled by corporate environmental abuse, everything from unchecked pollution to unpunished disasters and the growing threat of climate change. She pursued a law degree at Stanford Law School, later led the Natural Resources Defense Council (NRDC), and now serves as the Director of Global Climate Strategies for a climate non-profit.

At school and in academia. What research are people working on? What subjects interest you? Which professors are tackling interesting problems and pushing exciting boundaries?

For example, a friend of mine was inspired by her Child Development Psychology professor, who encouraged her to pursue graduate school. With support from that professor, my friend earned a spot in a top PhD program at the University of Michigan. Today, she’s a professor of Child and Adolescent Development in California, researching educational outcomes for first-generation Latino students.

At work. What’s inefficient or frustrating? What tools would make life easier? What solutions are missing that need to be built?

For example, a friend of mine noticed how tedious and frustrating it was to onboard contractors. So, he launched a startup to streamline everything from interviews to payroll. In 2021, he sold that same startup to Workday for $500 million USD.

For me, I'm driven by technological innovations that improve society (Product Management + Strategy) and working to ensure the responsible deployment of that technology to keep the world safe (Trust & Safety). For my wife (the INTJ), her focus is on ensuring technology is used fairly and that personal data isn’t exploited or misused (she's a lawyer that works in data privacy).

You won’t know how good you are at solving problems until you identify your strengths. Then: research, experiment, fail, learn, grow, and repeat. Without data, there are no new insights. Get out there, try something, and come back with real-world feedback.

[justinspoliticalcorner]

Erin Reed at Erin In The Morning:

On Tuesday, the Supreme Court gave the green light for the Trump administration’s ban on transgender military service to take effect—staying lower court rulings that had found the policy blatantly unconstitutional. Those courts had determined the ban violated equal protection guarantees and was driven by anti-transgender animus, not military necessity. The policy brands transgender people as inherently “dishonorable” and “undisciplined” for no reason other than their gender identity. With the high court’s decision, the administration now has license to purge transgender service members—an alarming signal that the Supreme Court may be willing to overlook constitutional protections for trans people in future cases. Only three justices—Kagan, Jackson, and Sotomayor—dissented from the Supreme Court’s decision to let the Trump administration begin purging transgender service members. The ruling followed the Ninth Circuit’s refusal to stay a lower court decision that had blocked the ban, with the district judge finding it likely unconstitutional and a violation of due process. That judge condemned the policy for imposing “demeaning, cruel, and unsupported badges of infamy” on transgender troops. Nevertheless, the Supreme Court has now cleared the way for the ban to take effect while the case proceeds, granting an expedited hearing on the dubious claim that the presence of transgender people in the military constitutes a national emergency. Though technically a temporary measure—the decision sends the case back to the Ninth Circuit for full review—the calling it temporary is a distinction without a difference. It grants the military immediate authority to discharge transgender service members, displacing them from their jobs, income, and housing. By the time the Ninth Circuit, and ultimately the Supreme Court, issues a final ruling, the damage will already have been done. Service members will have been removed not for misconduct or performance, but solely for being transgender. While the legal fight continues, and some may still hope for a reversal, the Court’s willingness to greenlight these separations now offers a sobering preview of where it likely stands on the constitutional rights of transgender people—and the likely outcome of the case. Many legal observers have pointed to this case as one of the most clear-cut opportunities for a neutral court to affirm the constitutional rights of transgender people. That’s because the Trump administration made little effort to conceal the unconstitutional animus driving its executive order. The policy declares that for transgender people, “the adoption of a gender identity inconsistent with an individual’s sex conflicts with a soldier’s commitment to an honorable, truthful, and disciplined lifestyle, even in one’s personal life.” The message was unmistakable—and so overtly discriminatory that U.S. District Judge Ana Reyes, in a separate case blocking the policy, described it as “soaked with animus.” “Neither document contains any analysis nor cites any data,” Reyes wrote. “They pronounce that transgender persons are not honorable, truthful, or disciplined—but Defense counsel concedes that these assertions are pure conjecture…. Its language is unabashedly demeaning, its policy stigmatizes transgender persons as inherently unfit, and its conclusions bear no relation to fact… Thus, even if the Court analyzed the Military Ban under rational basis review, it would fail.” If implemented broadly, the ban will have immediate and damaging consequences for both transgender service members and military readiness across the United States.

[...] The case now returns to the Ninth Circuit, which will determine whether the military can legally separate transgender service members—a question with enormous constitutional stakes, even as discharges are expected to begin. Meanwhile, the D.C. Circuit has stayed Judge Reyes’s ruling, allowing the ban to go into effect, though it leaves open the narrow possibility for appeals if separations proceed. In reality, that path is unlikely to succeed in the wake of the Supreme Court’s intervention. The immediate effect of the Court’s decision is clear: the ban can be enforced now. And in the coming days, transgender soldiers are likely to begin facing its devastating consequences firsthand.

The MAGA Majority on SCOTUS voted 6-3 to allow the bigoted ban on trans military servicemembers to take effect while appeals are still taking place.

See Also:

Law Dork: Supreme Court allows Trump's anti-trans military ban to go into effect

LGBTQ Nation: Supreme Court allows military to start kicking trans people out

The Guardian: US supreme court allows Trump trans military ban to take effect

The Advocate: BREAKING: Supreme Court allows Trump administration to enforce transgender military ban

HuffPost: Supreme Court Allows Trump Ban On Transgender Members Of The Military To Be Enforced

[self-loving-vampire]

You've posted about LLMs a few times recently and I wanted to ask you about my own case where the tool is abstract and should be whatever, but what if the entire tech industry is filled with misanthropic fast talking nerds whose entire industry is fueled by convincing finance ghouls to keep betting the gdp of Yemen that there will be new and interesting ways to exploit personal data, and that will be driven by the greasiest LinkedIn guy in the universe? Correct me if I'm wrong, but would it not be a decent heuristic to think "If Elon Musk likes something, I should at least entertain reviling it"? Moreover: "E=MC^2+AI" screenshot

Like-- we need to kill this kind of guy, right? We need to break their little nerd toys and make them feel bad, for the sake of the world we love so dear?

I get annoyed with moralizing dumbdumbs who are aesthetically driven too, so it is with heavy heart that giving these vile insects any quarter into my intellectual workings is too much to bear. I hope you understand me better.

I think you're giving people like Elon Musk too much influence over your thoughts if you use them as some kind of metric for what you should like, whether it's by agreeing with him or by doing the opposite and making his positive opinions of something (which may not even be sincere or significant) into a reason to dislike that thing. It's best to evaluate these things on their own merits based on the consequences they have.

I personally don't base my goals around making nerds feel bad either. I am literally dating an electrical engineer doing a PhD.

What I care about here is very simple: I think copyright law is harmful. I don't want copyright law to be expanded or strengthened. I don't want people to feel any kind of respect for it. I don't want people to figuratively break their toes punting a boulder out of spite towards "techbros". That's putting immediate emotional satisfaction over good outcomes, which goes against my principles and is unlikely to lead to the best possible world.

[whentherewerebicycles]

ok chipping away at this AI workshop and here is a first stab at articulating some learning goals. in this two-workshop series, I want students to:

explore and discuss the limits of AI as a research tool (including issues around AI hallucinations and “overcertainty”, sources consulted & source credibility, data privacy and security, etc)

develop concrete strategies for using AI more effectively in research contexts (including how to coach AI tools to give more rigorous search results + how to prompt AI to give substantive feedback rather than generating content for you)

differentiate between situations where using AI is shortchanging your learning/growth vs. helping you automate rote tasks that free up energy to do substantive work. maybe we’ll evaluate different hypothetical scenarios here and I’ll ask students to argue both sides before deciding on a stance… I think we can also work in some discussion here about the underlying emotional stuff that might drive us to use generative AI in inappropriate or unproductive ways—imposter syndrome, fear of falling behind or not measuring up to others, poor time management, etc.

practice having conversations about the use of AI in research with faculty mentors and peers (basically I want them to understand that adults are also learning this stuff in real time and also have a wide range of attitudes towards generative AI, and may not know how to have productive conversations about it with students… I certainly feel that way myself!! so I want to give them some tools for starting those conversations and clarifying mentor expectations around AI use)

can’t figure out how to articulate this as a learning outcome yet but I am hoping that we can do a mix of this focused work on “here are concrete strategies for dealing with these tools” + bigger-picture reflection on what learning is for and why we are personally driven to learn/develop expertise/create new knowledge. I want one of the big overarching aims of the summer seminar to be helping students articulate their identity, purpose, and values as researchers… and then we’ll think together about how all this skill development stuff we’re doing fits into that larger framework of why we care about this work and why we’ve chosen to pursue it.

[compneuropapers]

Interesting Papers for Week 2, 2025

A geometrical solution underlies general neural principle for serial ordering. Di Antonio, G., Raglio, S., & Mattia, M. (2024). Nature Communications, 15, 8238.

Beyond Neyman–Pearson: E-values enable hypothesis testing with a data-driven alpha. Grünwald, P. D. (2024). Proceedings of the National Academy of Sciences, 121(39), e2302098121.

Prefrontal and lateral entorhinal neurons co-dependently learn item–outcome rules. Jun, H., Lee, J. Y., Bleza, N. R., Ichii, A., Donohue, J. D., & Igarashi, K. M. (2024). Nature, 633(8031), 864–871.

Human brain state dynamics are highly reproducible and associated with neural and behavioral features. Lee, K., Ji, J. L., Fonteneau, C., Berkovitch, L., Rahmati, M., Pan, L., … Anticevic, A. (2024). PLOS Biology, 22(9), e3002808.

Distinct ventral hippocampal inhibitory microcircuits regulating anxiety and fear behaviors. Li, K., Koukoutselos, K., Sakaguchi, M., & Ciocchi, S. (2024). Nature Communications, 15, 8228.

Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter. Malamud, J., Guloksuz, S., van Winkel, R., Delespaul, P., De Hert, M. A. F., Derom, C., … Huys, Q. J. M. (2024). PLOS Computational Biology, 20(9), e1012457.

The homogenous hippocampus: How hippocampal cells process available and potential goals. McNaughton, N., & Bannerman, D. (2024). Progress in Neurobiology, 240, 102653.

Decision uncertainty as a context for motor memory. Ogasa, K., Yokoi, A., Okazawa, G., Nishigaki, M., Hirashima, M., & Hagura, N. (2024). Nature Human Behaviour, 8(9), 1738–1751.

Maintenance and transformation of representational formats during working memory prioritization. Pacheco-Estefan, D., Fellner, M.-C., Kunz, L., Zhang, H., Reinacher, P., Roy, C., … Axmacher, N. (2024). Nature Communications, 15, 8234.

Dense and Persistent Odor Representations in the Olfactory Bulb of Awake Mice. Pirhayati, D., Smith, C. L., Kroeger, R., Navlakha, S., Pfaffinger, P., Reimer, J., … Moss, E. H. (2024). Journal of Neuroscience, 44(39), e0116242024.

Contrastive learning explains the emergence and function of visual category-selective regions. Prince, J. S., Alvarez, G. A., & Konkle, T. (2024). Science Advances, 10(39).

Independent operations of appetitive and aversive conditioning systems lead to simultaneous production of conflicting memories in an insect. Rahman, S., Terao, K., Hashimoto, K., & Mizunami, M. (2024). Proceedings of the Royal Society B: Biological Sciences, 291(2031).

Effects of visual diet on colour discrimination and preference. Skelton, A. E., Maule, J., Floyd, S., Wozniak, B., Majid, A., Bosten, J. M., & Franklin, A. (2024). Proceedings of the Royal Society B: Biological Sciences, 291(2031).

Neural network architecture of a mammalian brain. Swanson, L. W., Hahn, J. D., & Sporns, O. (2024). Proceedings of the National Academy of Sciences, 121(39), e2413422121.

Saccadic “inhibition” unveils the late influence of image content on oculomotor programming. Taylor, R., Buonocore, A., & Fracasso, A. (2024). Experimental Brain Research, 242(10), 2281–2294.

Mental programming of spatial sequences in working memory in the macaque frontal cortex. Tian, Z., Chen, J., Zhang, C., Min, B., Xu, B., & Wang, L. (2024). Science, 385(6716).

Humans flexibly integrate social information despite interindividual differences in reward. Witt, A., Toyokawa, W., Lala, K. N., Gaissmaier, W., & Wu, C. M. (2024). Proceedings of the National Academy of Sciences, 121(39), e2404928121.

Different Sensory Information Is Used for State Estimation when Stationary or Moving. Wong, A. L., Eyssalenne, A. N., Carter, L., & Therrien, A. S. (2024). eNeuro, 11(9), ENEURO.0357-23.2024.

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations. Zada, Z., Goldstein, A., Michelmann, S., Simony, E., Price, A., Hasenfratz, L., … Hasson, U. (2024). Neuron, 112(18), 3211-3222.e5.

Geometric Scaling Law in Real Neuronal Networks. Zhang, X.-Y., Moore, J. M., Ru, X., & Yan, G. (2024). Physical Review Letters, 133(13), 138401.

[ixnai]

The allure of speed in technology development is a siren’s call that has led many innovators astray. “Move fast and break things” is a mantra that has driven the tech industry for years, but when applied to artificial intelligence, it becomes a perilous gamble. The rapid iteration and deployment of AI systems without thorough vetting can lead to catastrophic consequences, akin to releasing a flawed algorithm into the wild without a safety net.

AI systems, by their very nature, are complex and opaque. They operate on layers of neural networks that mimic the human brain’s synaptic connections, yet they lack the innate understanding and ethical reasoning that guide human decision-making. The haste to deploy AI without comprehensive testing is akin to launching a spacecraft without ensuring the integrity of its navigation systems. The potential for error is not just probable; it is inevitable.

The pitfalls of AI are numerous and multifaceted. Bias in training data can lead to discriminatory outcomes, while lack of transparency in decision-making processes can result in unaccountable systems. These issues are compounded by the “black box” nature of many AI models, where even the developers cannot fully explain how inputs are transformed into outputs. This opacity is not merely a technical challenge but an ethical one, as it obscures accountability and undermines trust.

To avoid these pitfalls, a paradigm shift is necessary. The development of AI must prioritize robustness over speed, with a focus on rigorous testing and validation. This involves not only technical assessments but also ethical evaluations, ensuring that AI systems align with societal values and norms. Techniques such as adversarial testing, where AI models are subjected to challenging scenarios to identify weaknesses, are crucial. Additionally, the implementation of explainable AI (XAI) can demystify the decision-making processes, providing clarity and accountability.

Moreover, interdisciplinary collaboration is essential. AI development should not be confined to the realm of computer scientists and engineers. Ethicists, sociologists, and legal experts must be integral to the process, providing diverse perspectives that can foresee and mitigate potential harms. This collaborative approach ensures that AI systems are not only technically sound but also socially responsible.

In conclusion, the reckless pursuit of speed in AI development is a dangerous path that risks unleashing untested and potentially harmful technologies. By prioritizing thorough testing, ethical considerations, and interdisciplinary collaboration, we can harness the power of AI responsibly. The future of AI should not be about moving fast and breaking things, but about moving thoughtfully and building trust.

[dragon-in-a-fez]

Hi again dragon-in-a-fez! I have a question. I'm taking a course on childhood abuse and trauma at my college, and it's been a little tense but peaceful. My professor (has a child/developmental psychology PhD) has mentioned that the majority of parents do NOT abuse children, although child abuse is not rare. I did share with him studies of how violent discipline is still common around the world*, and we both agree spanking is obviously abuse. But he still says no, the majority of parents are not abusive, and I can't make general statements.

Today we had a class about sexual abuse and we discussed a little on how we could possibly know or decide what is abuse. We both mentioned if the kid feels discomfort or pain as one criterion, as is the case with spanking. And by that standard also, he mentioned if a parent is giving a child a shower/wiping their butt after pooping, the parent is not abusive if they have to touch the child's genitals but get no sexual pleasure out of it, and the child doesn't feel bad. But then he mentioned how there are things we make kids do that he says are not abusive, like having them do homework or go to bedtime. He then went from there when i asked him about making a child hug/kiss a parent/relative. He said that's totally different from sexual abuse since parents are resoonsible for teaching children socially acceptable behavior and norms. We also mentioned how sexual abuse is defined when it's deemed "inappropriate" (with the implication being that is what society and social norms say).

But i have some problems with my professor's takes, although i admit he knows 100x more than i do. Im just a student. First of all, since when did social norms ever dictate right from wrong? "Socially appropriate" doesn't rqual right, "socially inappropriate" doesn't equal wrong. Second, social norms and the very idea of what is "socially approproate/inappripriate" can be easily weaponized against chilldren. After all, parents/adult control society and are the ones dictating social norms in the first place. For example, like i just said, its still socially appropriate to make kids hug/kiss against their will, as well as to spank them. Its seen as socially inappropriate and bad manners for kids to refuse hugs/kisses. Its socially inappropriate for kids to say fuck or shit, but its socially appropriate to slap or spank kids who say fuck/shit or for any other perceived offense, or make them ingest soap. Its seen as socially inappropriate/impolite to talk about sex, especially with children. Even tho that knowledge could very well save children from abuse.

But anyways, Im no expert, though im still a lil skeptical of what my professor has said. How would you respond, as a professor in children's studies? I look forward to your take on this, and I trust your expertise. Do you think you can cite studies/reports too? I think my professor would be happy to look more into what I've been saying. Thanks for listening!

/*https://publications.aap.org/pediatrics/article/137/3/e20154079/81439/Global-Prevalence-of-Past-year-Violence-Against?autologincheck=redirected

http://globalreport.knowviolenceinchildhood.org/global-report/time-end-violence-childhood/

well, for starters, the last time I saw a survey of parents that asked if they'd ever hit their children, 58% said yes (this was in the UK - it's higher in the US but admittedly my knowledge there is based on older data). so you can't simultaneously acknowledge that hitting children is abuse and believe the majority of parents aren't abusive. like, that's just math. that's one where you can probably find data pretty easily.

the rest of it isn't going to be so data-driven. let me take a step back and explain what I mean.

one of the things I encourage my students to do is challenge how we decide what is child abuse and what isn't. historically, that determination has been made based on a question of whether something will harm development or lead to worse outcomes for a hypothetical future adult. (this goes back to the earliest child protection laws, which were framed as religious duties not to endanger the child's immortal soul.) this is still the way child abuse is often operationalised, as a question of "this thing is abusive if it will make the kid a worse adult in some measurable way".

to me it's obvious that that's bonkers. what we should be doing is defining child abuse the way we define other forms of abuse: as improper treatment of a person, in relation to that person's human rights to dignity, safety, and self-ownership.

I think your professor is probably stuck in that former mindset, and their logic is going something like: we don't have objective evidence that making kids hug people causes lasting harm into adulthood, and culturally we believe it does make kids grow up into adults who can connect with others, so the net impact on development is positive, so it's not abuse.

when someone has that mindset about spanking, it's (comparatively) easy to push back on, because all you need to do is point to decades of strong research evidence that spanking is developmentally harmful. so it's theoretically possible to get them to understand that it's abusive without actually needing to challenge their overall mental framework of abuse.

for something like consent to affection, the counterargument is more difficult. it needs to start with: you have to rethink how you're making your determinations about abuse. you have to see abuse not in terms of developmental harm, but in terms of denial of personhood. for someone who's been mired in a developmentalist view of childhood for a long career, that can be really difficult. I don't know that I have any specific advice - except to remain steadfast in your person-centred framework of how we should treat each other, and understand that you're not wrong and you're not alone.