According to a study¹ conducted by the Indiana University Kelley School of Business, diversity in terms of gender, race, and ethnicity has proven to be beneficial for companies operating in the United States.

However, the research also highlights the significance of diverse educational, industrial, and organizational backgrounds among managers and board members in fostering innovation in research and development (R&D), thereby generating both economic and social value.

“We looked at their experiences and not just their demographic background—the more functional aspect of diversity. We looked at outcomes and found radical innovation when directors had more diverse experience, helping to guide firms toward more cutting-edge exploration and success,” the researchers explain.

Broad experience

A broader range of educational backgrounds within corporate leadership can offer valuable perspectives and a more expansive outlook when confronted with uncertain circumstances.

Numerous companies are now addressing market and regulatory demands by actively seeking to enhance the demographic diversity of their corporate boards. The reliance on a narrow set of qualifications and traditional pedigrees for directorship roles restricts the pool of potential candidates, resulting in scarcity for individuals who are women or belong to racial and ethnic minority groups.

“Noting the benefits of diverse experiences in the board room, corporate executives can search beyond the tradition director pedigree (e.g. Ivy League-educated financiers), where female and minority individuals remain underrepresented,” the researchers explain. “In doing so, the firm can find more qualified candidates to assemble a demographically and intellectually diverse board, thus cultivating an inclusive corporate culture conducive to shareholder and stakeholder value creation.”

Limited supply

For instance, the researchers found that the relatively limited supply of women in the boardroom rendered them a scarce commodity, so if you have a single woman sitting on the boards of 20 companies, she’s likely to be spread extremely thinly and not as useful in her contributions.

The study encompassed an extensive dataset comprising over 11,000 observations of 971 firms that had filed one or more patent applications during the period spanning 1996 to 2014.

One notable case highlighted in the research paper exemplifies a highly innovative company that prioritizes diverse experiences and a collective range of expertise within its boardroom. Moderna, a prominent pharmaceutical and biotechnology firm, adopted an unconventional approach utilizing RNA technology to develop one of the COVID-19 vaccines.

Their advisory board consists of individuals with educational backgrounds in fields such as medical sciences, economics, journalism, and finance. Similarly, other companies may include board members who bring their expertise from areas like computer science and political science.

Supporting innovation

“From leadership’s perspective, critical thinking is very important in terms of guiding companies to take higher risks and evaluating the trajectory of their R&D efforts,” the researchers explain. “If some of the people in the board room aren’t trained in the more pragmatic disciplines—such as someone trained in journalism—it helps them to think between the lines and beyond the face value of a decision.”

This is crucial, as radical innovation is inherently riskier, so it’s important that directors are able to have an open and long-term mindset to help firms navigate this uncertainty.

“While there can be tension between short- and long-term value creation, it is not irreconcilable,” the researchers conclude. “Firms can potentially achieve the best of both worlds by recruiting female and minority directors with non-traditional experiences, who are likely mindful of both current shareholder value and future growth opportunities.”

Article source: Diverse Boards Are More Innovative.

Header image source: Memento Media on Unsplash.

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In dynamic and ever-evolving professional settings, employers are always on the hunt for innovative approaches to acknowledge employees within the workplace.

Nevertheless, recent findings¹ from the University of Waterloo indicate that public peer recognition, while well-intentioned, may inadvertently trigger unfavorable consequences. The study suggests that the facilitation of comparisons among employees through such recognition can lead certain individuals to perceive themselves as being subjected to unjust treatment.

“Employers have sought out various peer recognition systems in an effort to promote employee helping behavior,” the researcher explains. “When employees feel that they deserve recognition from their peers but do not receive it, employees can conclude that they are unfairly treated, and this makes employees less willing to help other co-workers, not only the co-worker they feel treated them unfairly.”

Unfair situations

In practical terms, situations perceived as unfair by employees can arise when there are discrepancies in defining the criteria for behavior worthy of acknowledgment during public peer recognition. Furthermore, some employees may exhibit a tendency to offer recognition exclusively to those with whom they share close relationships.

To delve deeper into this phenomenon, a research endeavor conducted within a three-employee context—the recognizer, the helper, and the worker—examines the impact of peer information divulged through peer recognition systems on subsequent willingness to assist.

The study employs a scenario where both the helper and the worker extend their aid to the recognizer, yet only the helper receives recognition from the recognizer. Notably, the worker demonstrates a diminished willingness to assist both the recognizer and the helper when perceiving their initial assistance to surpass that of the helper.

Willingness to help

Conversely, the worker exhibits a higher level of willingness to help the helper when perceiving their initial assistance as being less than that of the helper. Evidently, the worker’s reduced inclination to aid the helper stems from a reciprocal response to the recognizer’s failure to provide recognition.

These findings represent the inaugural empirical evidence highlighting the adverse ramifications of peer recognition systems on helping behavior. They carry significant implications for employers seeking to implement peer recognition strategies within the workplace. Although peer recognition is often advocated as a tool to foster a more altruistic attitude among employees, this study underscores the importance of vigilance among managers regarding the potential drawbacks associated with its implementation.

“The research provides a first step in cautioning managers about a potential unintended consequence of using public peer recognition, and that is the perceived unfairness that reduces helping behavior,” the author concludes. “It may be helpful for managers to communicate with their employees and come up with some agreed-upon guidelines on what should be recognized via public peer recognition and what does not need to be recognized via public peer recognition.”

Article source: Peer Recognition Programs Carry Risks At Work.

Header image source: Marco Verch on Flickr, CC BY 2.0.

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Earlier this year, I pondered what impact the new wave of AI tools might be having on our ability to think and be creative. The article questioned the traditional narrative, that AI-based tools free us from drudgery and thus give us more time to think and create.

The article was based on studies suggesting that often we become slaves to technology, with our time spent servicing it rather than being liberated by it. It’s a narrative contested by a recent study¹ from the University of Southern California, which highlights how AI can support our creativity, albeit only under certain conditions.

“We found that AI assistance changes job design by intensifying employees’ interactions with more serious customers,” the researchers explain. “This change enables higher-skilled employees to generate innovative scripts and develop positive emotions at work, which are conducive to creativity.”

Supporting work

The findings are based on work undertaken in a telemarketing firm. Forty sales agents, comprising the top third and bottom third performers, were selected to receive AI assistance in their interactions with a total of 3,144 customers.

Traditionally, the company followed a two-step approach to its sales process. Firstly, employees would contact customers to provide general information and assess their level of interest, aiming to generate sales leads defined as individuals who expressed interest in learning more about the product without committing to a purchase.

The lead generation process involved the use of scripted interactions, with uninterested customers being filtered out. Subsequently, employees would engage with the leads to better understand their requirements and persuade them to make a purchase, such as applying for a credit card, as part of this experiment.

AI assistance

To facilitate the first step of the experiment, the company adopted AI conversational bot technology, leveraging cutting-edge advancements in deep-learning neural networks, voice recognition algorithms, and natural language understanding via bidirectional encoder representations from transformers. The AI bot had undergone extensive training using terabytes of telemarketing call data, enabling it to engage in natural, human-like conversations with customers.

Remarkably, the AI technology performed so well that during the initial two- to three-minute conversations, nearly 97% of customers were unable to discern whether they were interacting with a human sales agent or the AI bot.

The results were indeed impressive. Approximately half of the customers who made calls were confirmed as sales leads. What’s more, customers who received assistance from AI-assisted sales agents were almost twice as likely to make a purchase compared to those served solely by human sales agents.

Successful resolution

With the aid of AI, the average agent experienced a 2.3-fold increase in successfully addressing questions they had not previously been trained for. In the case of top-performing agents, the assistance provided by AI resulted in a 2.8-fold improvement in their ability to respond to untrained questions, in comparison to their performance without AI assistance.

“AI can help your employees become more creative at work, but it only applies to your higher-skilled employees. With AI eliminating menial drudgery, those higher-skilled employees can use their potential to achieve more creative outcomes. However, your lower-skilled employees might not simply have the ability to achieve creative outcomes,” the researchers explain.

Suffice it to say, this doesn’t mean that you should dismiss those lower-skilled employees, and the researchers accept that there may be numerous other ways in which such people can improve their performance, whether through mentoring, training, or support from peers.

Indeed, AI can help those people too, as the study found that because the chatbot took care of customers who were less serious about the products, the human agents were left with those who were easier to serve and didn’t require as much persuasion.

The jury remains out

The introduction of AI in customer service has garnered mixed reactions, particularly from lower-skilled workers who find that it complicates their tasks rather than simplifying them. Many customers tend to disconnect during the initial stages of a call, leading to frustration among these workers.

They express that AI exacerbates the difficulty of their job, as they struggle to provide the necessary information to address customers’ needs effectively. Consequently, this demoralizes them, amplifying the perceived intensity of their work.

Unlike before, where interactions may have been mundane but less mentally demanding, every call now requires active engagement and the ability to serve customers based on their specific requirements.

The need for a sober assessment

According to the researchers, it is common for individuals to perceive AI as a dangerous threat to human existence. However, there are numerous ways in which technology can assist and empower humans. Understanding the processes that are best suited for such utilization becomes crucial.

One notable example lies in the realm of recruitment. Increasingly, recruiters have employed AI for initial screening, allowing human experts to handle subsequent interview stages. LinkedIn surveys have reported that 67% of hiring managers view AI as a valuable time-saving tool in this context. Similarly, in healthcare services, where triage processes are employed to categorize patients, AI has proven helpful in supporting employees with medical chart coding.

These instances illustrate how AI can be harnessed to augment human capabilities and enhance efficiency in certain processes. It is essential to discern which areas are most appropriate for the integration of technology to strike a balance between automation and the human touch.

Article source: Using AI To Augment Creativity.

Header image source: Alexandra Koch on Pixabay.

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Research¹ conducted by ESMT Berlin reveals that while machines are capable of making superior decisions compared to humans, humans often struggle to recognize when a machine’s decision-making is more accurate. This tendency to override algorithmic decisions to the detriment of outcomes is referred to as algorithm aversion.

While algorithm aversion has been commonly attributed to a fundamental mistrust of machines, this study introduces a new perspective. The research highlights that the context in which human decision-makers operate can also hinder their ability to discern whether machines generate better recommendations.

Working together

To investigate the circumstances under which a human decision-maker, responsible for supervising critical machine decisions, can effectively assess the quality of machine-generated recommendations, the researchers developed an analytical model.

In this model, a human decision-maker oversaw a machine entrusted with vital choices, such as determining whether a patient should undergo a biopsy. Subsequently, the human decision-maker made the optimal selection based on the information provided by the machine for each task.

The study found that when a human decision-maker followed the machine’s recommendation and achieved a positive outcome, their trust in the machine increased.

However, in situations where the human decision-maker did not observe the correctness of the machine’s recommendation, such as when they chose not to pursue further actions, trust remained unchanged, and no valuable lessons were gained.

Assessing the machine

This interplay between the human’s decision and their assessment of the machine engenders biased learning. Consequently, over time, humans may fail to acquire the proficiency needed to effectively utilize machines.

These findings clearly demonstrate that the tendency to override algorithmic decisions is not solely driven by an inherent mistrust of machines. Rather, the accumulation of biased learning, facilitated by consistent overriding, can lead to the erroneous and inefficient deployment of machines in decision-making processes.

“Often, we see a tendency for humans to override algorithms, which can be typically attributed to an intrinsic mistrust of machine-based predictions,” the researchers explain. “This bias, however, may not be the sole reason for inappropriately and systematically overriding an algorithm. It may also be the case that we are simply not learning how to effectively use machines correctly, when our learning is based solely on the correctness of the machine’s predictions.”

The findings remind us that people often lack sufficient trust in technology’s ability to make effective decisions, but without this, we can’t really effectively utilize the capabilities technology has.

“Our research shows that there is clearly a lack of opportunities for human decision makers to learn from a machine’s intelligence unless they account for its advice continually,” the authors conclude. “We need to adopt ways of complete learning with the machines constantly, not just selectively.”

Article source: Humans and Machines Still Struggle to Cooperate on Decision Making.

Header image source: Created by Bruce Boyes with Perchance AI Photo Generator.

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Misinformation about scientific topics remains a key concern for society. A recent paper¹ from the University of Pennsylvania looks at the most effective way for misinformation to be corrected.

The researchers embarked on a comprehensive meta-analysis, employing rigorous quantitative methods to synthesize a wealth of prior research. This encompassed an impressive sample size of 60,000 participants involved in 74 distinct experiments. In each experiment, the focus was either to evaluate belief in misinformation concerning scientific matters or to present misinformation as accurate before subsequently introducing corrective measures.

More reliable information

While, on the whole, these corrective interventions fell short of achieving their intended outcomes, certain noteworthy patterns emerged. Specifically, the effectiveness of the corrections was enhanced under certain circumstances: when the subject matter of the correction possessed a more emotionally positive connotation compared to the initial misinformation, when the correction aligned with the ideological predispositions of the recipients, when the issue at hand was not marred by intense political polarization, and when the correction offered ample and comprehensive details elucidating the falsity of the earlier claims.

Significantly, the researchers observed that endeavors aimed at debunking misinformation relating to scientific domains, when viewed collectively, did not yield satisfactory results.

“Therefore, most of the science-relevant misinformation goes uncorrected even when a debunk is presented. People believe in the misinformation as much before as after the debunk,” the researchers explain. “This is quite notable, because corrections in other domains, such as reports about an accident or political event, do reasonably well, as shown by past research. However, this does not occur in the domain of misinformation about science.”

Is it possible?

The researchers embarked upon their study with a dual purpose: firstly, to assess the feasibility of correcting misinformation, and secondly, to discern the comparative effectiveness of various types of corrective measures.

In pursuit of these objectives, the team initially sought to ascertain whether negative or neutral misinformation proved more amenable to correction. Their inquiry substantiated that positive misinformation, characterized by its ability to engender positive emotions and generate favorable sentiments towards oneself, one’s prospects, or the world at large, presented a greater challenge in terms of rectification than negative misinformation did.

“We humans like to keep our rose-tinted glasses on, and we are resistant to debunking pseudoscience that feels good,” they explain. “It is far easier to correct hype about a chemical spill that didn’t happen than about deforestation that is happening. The reason is that it’s more pleasant to move from pessimistic to optimistic news rather than the other way around.”

Correcting the record

The quest to determine the most effective corrective messages also occupied the researchers’ attention. Their findings revealed that when a correction provides a comprehensive and detailed explanation, it enhances the likelihood of audience receptivity and successful debunking of the misinformation. This process unfolds in two stages.

Initially, the specific details and information contained within the correction furnish respondents with a fresh framework through which they can comprehend the event described in the misinformation. Subsequently, this new representation of the factors that led to the event supplants the initial framework established by the misinformation.

In addition, the researchers explored whether an individual’s attitudes or beliefs influenced the efficacy of correcting science-related misinformation. Their investigations disclosed that when a debunking contradicts people’s ideological leanings, recipients are more inclined to reject the correction and fortify their support for the misinformation.

Ideology matters

For instance, a person harboring left-leaning ideological inclinations is predisposed to accept a correction refuting claims that challenge the existence of climate change. Conversely, when a debunking clashes with people’s ideological convictions, they are more prone to dismiss the correction and reinforce their allegiance to the misinformation.

The presence of political polarization surrounding the scientific issue under discussion also emerges as a crucial factor. The study revealed that when a topic becomes polarized, as exemplified by the contentious realm of COVID-19 vaccination, corrections often falter.

Nevertheless, strategies exist to rectify misinformation, provided that obstacles are duly acknowledged and circumvented. The authors recommended several approaches, including employing detailed corrections, fostering familiarity with the topic among the audience, and endeavoring to dissociate discussions on science from the realm of politics to reduce polarization. However, if the topic is already entrenched in political polarization, the correction must be formulated in a manner that aligns with the recipient’s political inclinations.

Article source: How Best To Correct Scientific Misinformation.

Header image source: Created by Bruce Boyes with Perchance AI Photo Generator.

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Research conducted by the University of Cambridge reveals a concerning trend hindering the UK’s ability to address pressing issues such as public health and climate change. The study¹ suggests that policymakers often disregard existing evidence when formulating policies, impeding progress in these critical areas.

According to the research findings, this “evidence-neglect” arises from the incentive structures that reward politicians for setting ambitious policy objectives while simultaneously discouraging the implementation of necessary measures to achieve them. Furthermore, conflicting political ideologies and interests further contribute to this challenge, impeding the adoption of effective policies.

Overcoming the flaw

The author proposes two key measures. Firstly, involving citizens more actively in the policy-making process would ensure that their interests take precedence. Secondly, enhancing the accountability of politicians through the implementation of legally binding frameworks for all stages of policy-making would promote responsible decision-making.

Notably, successive UK governments have pledged to tackle major societal issues by setting ambitious targets. These objectives encompass significant milestones such as reducing childhood obesity by 50% before 2030, eradicating smoking by 2030, narrowing the gap in healthy life expectancy by 2030, and achieving net zero carbon emissions by 2050.

“None of these ambitions is on course,” the author explains. “Of course, scientific evidence is just one of many sources of information for policymakers to consider, but neglecting evidence is a sure-fire route to unsuccessful policymaking.”

Poor progress

Forecasts paint a worrisome picture, suggesting that the goal of reducing childhood obesity by 50% by 2030 may fall short, with the likelihood of a doubling rather than a halving of cases during that period. Similarly, the eradication of smoking, initially targeted for 2030, appears to face a delayed realization, now projected to extend beyond 2050.

Furthermore, while the gap in healthy life expectancy between regions is predicted to narrow by 2030, subsequent estimations indicate a potential increase of five years by 2035. These trends suggest substantial challenges in meeting these ambitious objectives.

Realizing each of these aspirations necessitates sustained alterations in various sets of behaviors encompassing individuals across different socio-economic groups. These encompass dietary choices, consumption patterns, tobacco use, and transportation habits.

Lack of evidence

“There are many possible reasons why these policy ambitions are so far off-track, but chief among them is the neglect of evidence, particularly around achieving sustained changes in behavior across populations,” the author continues.

“Put simply, these failures are baked-in, given the policies designed to achieve these ambitions are based on interventions that cannot achieve the change required.”

Politicians are often incentivized to pursue ambitious goals, especially if they’re part of election pledges or are designed to achieve positive publicity. Against this, they can also discourage the kind of policies designed to achieve those goals.

“Fear of electoral damage plays a role here,” the author explains. “Take taxes on tobacco, alcohol, junk food and carbon emissions: these are among the most effective interventions for improving health and the climate, but they are unpopular with the public and so politicians are unwilling to adopt them.”

Resistance to progress

The implementation of such policies may encounter not only public resistance but also opposition rooted in political interests and ideologies. One such ideology is neoliberalism, which advocates for limited government involvement in the economy and public policy, placing greater emphasis on individual responsibility for achieving well-being, wealth, and happiness. Within this framework, government interventions are often portrayed as intrusive “Nanny Statism.”

Moreover, certain industries have a vested interest in promoting personal responsibility, as it dissuades politicians from adopting effective policies that could potentially impede their interests. Industries that stand to be affected by measures aimed at reducing the consumption of fossil fuels, tobacco, alcohol, meat, and unhealthy food often cast doubt on the efficacy of such policies. They employ various lobbying tactics to sway governmental decision-makers, presenting arguments that support the maintenance of the status quo and align with their business objectives.

“There are no quick or single fixes to overcoming these problems, but there are two changes which could help: engaging citizens more in priority setting and policy design, and increasing the accountability of politicians through introducing legally-binding systems for reporting progress on policy ambitions,” the author adds.

Next steps

Policymakers have a range of options at their disposal when it comes to engaging citizens. These options include surveys, focus groups, town hall meetings, citizen assemblies, and collaboration with civil society organizations. By adopting such an approach, policymakers can potentially mitigate the political repercussions of unpopular policies.

This is achieved by exposing citizens to evidence that demonstrates the effectiveness of these policies. Numerous studies have consistently shown that such exposure tends to increase support for these policies. In fact, policies crafted with citizen engagement tend to garner more public backing, as they are perceived to be fairer and more likely to achieve their intended goals.

To address the issue of neglecting evidence, which is crucial for policy success, introducing legally binding systems for reporting policies and monitoring progress towards policy ambitions could prove highly impactful. By implementing such systems, policymakers can ensure that if progress veers off track, appropriate measures are taken to rectify the situation.

An illustrative example of this can be found in the recent Leveling Up strategy paper by the UK government. This paper outlined plans to establish a statutory obligation for the government to provide annual reports on progress towards accomplishing the Leveling Up missions. In conjunction with these plans, the government also released a set of metrics to gauge progress and evaluate the efficacy of the strategy.

“Although these requirements are by no means perfect, the legislation as drafted will at least allow parliament significantly more scrutiny of progress towards a government ambition than is often the case,” the author concludes. “Laudable policy ambitions to improve a nation’s health and protect life on the planet will remain unfulfilled ambitions unless and until evidence is given a more central role in the policy-making process.”

Article source: Ignoring Evidence Affects UK’s Ability To Respond To Major Challenges.

Header image source: Created by Bruce Boyes with Perchance AI Photo Generator.

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CEOs are only as strong as the teams they lead, so it’s vital that leadership teams not only feature the right individuals, but that those individuals work effectively together. In The Next Leadership Team¹ the University of Zurich’s Thomas Keil joins Marianna Zangrillo to outline the best way to ensure that the right leadership teams are forged. They describe three core approaches leaders can take:

• Team of Stars – This is when leaders focus on getting the highest quality individuals possible into the leadership team. It’s an approach that is characterized by competition and individual performance, with minimal collaboration between units. It can help to ensure rapid decision-making but also runs the risk of being heavily disrupted by political wrangling.
• Synergistic Team – By contrast, a synergistic team focuses far more on collaboration and has a more consensual decision-making process. The diversity of inputs can lead to better decisions, while this can also improve the implementation of those decisions. Of course, it can also result in decision-making becoming laborious and team members becoming too complacent.
• Stretch Team – The final approach aims to strike a balance between the previous two approaches. It sees constructive conflict encouraged and combines star and team players. The aim is to mix individual initiative and coordination in a bid to limit the negative aspects of the previous two approaches while retaining their benefits. The betwixt, and between approach can dissuade those who are either star or team players from wanting to join, however, with mediocre outcomes a real risk.

The three groupings are the result of a ten-year research program into how different organizations have managed to build, organize, and manage leadership teams.

Article source: 3 Approaches to Forming a Leadership Team.

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In a recent article, I explored research looking at the introduction of automation into the workplace. The study found whereas the technology was largely sold in terms of its ability to save time and make workers more productive, this wasn’t always the case as workers would spend a lot of time making sure that data and conditions were right for the machine.

Research¹ from ESMT Berlin comes to a similar conclusion, as while introducing machine learning was shown to improve the accuracy of decision-making, it also resulted in extra cognitive effort required by workers when making those decisions.

Introducing AI

The researchers sought to investigate the impact of machine-based predictions on human decision-making processes and outcomes. Notably, the study found that the use of machines increases the workload of human decision-makers, particularly when they are cognitively constrained, such as when they are under time pressure or multitasking.

As a result, the introduction of AI to alleviate workload during high-pressure situations may actually lead to increased cognitive effort for the human decision-maker.

Moreover, the study revealed that while machine input generally improves the overall accuracy of human decisions, it can also increase the likelihood of specific types of errors, such as false positives.

Making decisions

To compare human-only decision-making to machine-aided decision-making, the researchers employed a machine-learning model to identify differences in accuracy, propensity, and the levels of cognitive effort exerted by humans.

“The rapid adoption of AI technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks,” the researchers explain. “However, when used alongside human rationale, machines can significantly enhance the complementary strengths of humans.”

The study highlights the considerable benefits of human-machine collaborations in professional settings, according to the researchers. While machines can deliver highly precise information, it remains crucial for humans to exercise their cognitive abilities in assessing their own information and comparing it to the machine’s recommendations before making a final decision.

Cognitive effort

Notably, this cognitive effort becomes even more critical when humans face time pressures or other constraints that demand a prompt decision.

The researchers emphasize that despite the undeniable value of machines, they should not be viewed as a panacea for all decision-making challenges.

Instead, humans must be vigilant in assessing the output provided by machines and ensuring that it aligns with their own conclusions. By doing so, professionals can leverage the strengths of both humans and machines to achieve optimal outcomes.

“Machines can perform specific tasks with incredible accuracy, due to their incredible computing power, whilst in contrast, human decision-makers are flexible and adaptive but constrained by their limited cognitive capacity – their skills complement each other.”, the researchers explain. “However, humans must be wary of the circumstances of utilizing machines and understand when it is effective and when it is not.”

Influencing performance

Drawing on the case of doctors and patients, the researchers’ recent findings indicate that incorporating machines into diagnostic processes can enhance accuracy and reduce the number of misdiagnosed patients.

However, in situations where disease incidence is low and time is limited, introducing machines may actually increase the number of misdiagnosed patients and heighten the cognitive effort required to arrive at a diagnosis due to the ambiguity that machine input can introduce.

The researchers note that their study offers both optimism and caution for those seeking to implement machines in professional settings. On the positive side, incorporating machine input tends to improve overall accuracy and reduce error rates, particularly when the machine’s predictions align with what humans expect. In such cases, the human decision-maker becomes more “efficient” by reducing their cognitive effort.

A mixed bag

Yet, the researchers caution that integrating machine-based predictions into human decision-making is not always advantageous in terms of reducing errors or cognitive effort. In fact, introducing machines may even lead to an increase in certain error types and prolong the time and cognitive effort required to make a decision.

These findings underscore the crucial role that machine-based predictions play in human judgment and decision-making. They provide valuable insights into when and how machine input should be incorporated and guide the design of effective human-machine collaborations.

Article source: Machine Learning Can Improve Accuracy But Also Increase Workload.

Header image source: Created by Bruce Boyes with Perchance AI Photo Generator.

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When academia and business converge, it piques interest. In their recent book Bridgebuilders: How Government Can Transcend Boundaries to Solve Big Problems, Professor Donald Kettl, renowned for his work Escaping Jurassic Government: How to Recover America’s Lost Commitment to Competence, and William Eggers, the executive director of Deloitte’s Center for Government Insights, bring a unique perspective.

They confess to having been in the realm of enhancing government efficiency and effectiveness for longer than they care to admit. They have witnessed an array of reforms aiming to expand, contract, devolve, privatize, and rewire government.

However, they cannot ignore the prevailing sense that government programs frequently fall short of their intended impact. Whether addressing homelessness, opioid abuse, crime, or immigration, the government often struggles to fulfill its promises.

The authors attribute this predicament to the traditional vending-machine model of government, where a problem is identified, an organization is established to address it, and money is allocated with the expectation of results. Alas, this model no longer suffices, as funds flow in, but results do not adequately materialize.

Solving problems in a complex world

To better enable government to solve problems in a complex world, they identify ten crucial behaviors that governments need to adopt:

1. Knock down barriers, as most problems will involve stakeholders from across society, so it’s important that government is able to act effectively with those from profit, non-profit, and academic sectors.
2. Seek mutual advantage, with this especially important when projects have multiple stakeholders who will need to have common strategies.
3. Nurture private partners, as it’s vital that private partners are instilled with a public spirit for success to be achieved.
4. Build trustworthy networks, because developing trust in government will require collaboration across sectors.
5. Grow catalytic government, as governments usually do more to shape and integrate solutions as they do to cultivate them themselves.
6. Focus on outcomes, because too often governments get bogged down by internal procedures rather than focusing on what they ultimately hope to achieve.
7. Make data the language, because its through data that both information is shared and actions are delivered.
8. Redefine accountability, so that rather than traditional, top-down authority, we have more modern systems.
9. Cultivate cross-boundary leaders, because when working across boundaries, leaders will need to learn to share responsibility.
10. Make the exceptional routine, as the new era of public management requires the ability to deploy bridgebuilding across government.

The authors attribute much of this shift in mindset to the COVID-19 pandemic. They highlight the success of Operation Warp Speed—a notable public-private collaboration that yielded tangible and significant results, with the development and distribution of vaccines.

Climate change, considered the wickedest problem of all, requires collective efforts. The authors contend that no individual, community, country, or continent can address this issue in isolation.

Public-private partnerships

These developments signify a broader trend of public-private mission-based transformations, countering Mariana Mazzucato’s notion that big government is the sole solution to wicked problems. The authors point out that even NASA has begun procuring space vehicles through a competitive marketplace and forming partnerships with various companies for its ambitious projects.

The authors present numerous arguments countering the supposed “failure of capitalism” put forth by Mazzucato. They highlight that since the late 1980s, business spending on research and development (R&D) has exceeded that of the federal government.

Additionally, foundations and private individuals are investing substantial capital in the pursuit of major innovations. Philanthropists in the United States have donated billions of dollars, with the Gates Foundation alone outspending the World Health Organization on global health issues.

Indeed, the authors assert that public policies necessitate private partners. They emphasize that venture capital is unlikely to fund highly risky endeavors such as deep space exploration, which typically falls under the purview of government. However, private investment excels in supporting early-stage innovations.

If this partnership can be effectively harnessed, it can lay the foundation for enhancing democratic governance in the twenty-first century.

Article source: Government Needs To Build Bridges To Solve Wicked Problems.

Header image source: Created by Bruce Boyes with Perchance AI Photo Generator.

So commonplace is it that growing businesses have to adapt to the changing environment that the “pivot” has become a part of entrepreneurial lore. A recent study¹ from Carnegie Mellon suggests that diverse teams are more likely to make successful pivots than their more homogeneous peers.

The research reveals that businesses established in dynamic environments tend to have a longer survival rate when their founding teams exhibit greater functional diversity. Conversely, functionally homogeneous teams, characterized by a limited number of distinct roles and perspectives, perform better in more predictable environments.

“Predicting the course of environmental change is difficult, but entrepreneurs who can synchronize their predictions with their decisions about team composition perform better,” the researchers explain.

Environmental changes

While previous research has focused on the influence of recent events on business ventures in response to environmental change, the interplay between a venture’s historical context, including the environmental conditions present during its inception, and performance outcomes remains unexplored.

“If environmental conditions at founding have a lasting influence on ventures’ internal processes, and recent environmental conditions determine the effectiveness of these processes, it is crucial for our theories of environmental change to account for both periods,” the authors continue.

In order to shed light on this issue, researchers combined studies on the lasting effects of founding conditions with research on the consequences of environmental change.

Team dynamics

The study surveyed over 140,000 alumni from Stanford University, resulting in a dataset of more than 1,000 entrepreneurs who founded ventures across 19 industries from 1960 to 2011, ranging from agriculture to energy and utilities. Respondents’ self-reported data were verified by cross-checking their information against lists of public and private companies.

The survey evaluated the duration of the ventures and whether they achieved positive liquidity events, such as an observed initial public offering or a merger or acquisition. Founders were also questioned about the functional roles present in their founding teams, including sales and marketing, general administration, operations, and finance.

The study found that functionally diverse teams, with members occupying a variety of roles and focusing on different areas such as sales, marketing, manufacturing, and distribution, were better equipped to cope with high environmental dynamism, which refers to the degree to which environmental changes are unpredictable for firms’ decision-makers. These teams also tended to exchange a large amount of information and engage in diverse perspectives.

However, the same founding conditions led to a reduced likelihood of positive exit when environmental dynamism increased over the lifetime of the venture. Overall, the study integrated insights from different research areas to provide a nuanced understanding of how the interplay of founding conditions and environmental change affects the survival and success of ventures.

“Our findings highlight the importance of firms developing capabilities to enable flexibility in decision-making processes, which are often inflexible, which limits firms’ ability to take advantage of unique opportunities provided by environmental change,” the researchers conclude.

Article source: Diverse Teams Help Organizations Adapt To Change.

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