The Fragmentation of Psychological Science

The phenomenon of repackaging old ideas, as seen across different eras in psychology (but exists in every discipline), raises questions about the practices of pop psychologists like (dare I suggest) Brené Brown, who often employs grounded theory—a methodology typically reserved for less understood phenomena—to restate established concepts under the guise of novelty. For example, Brown's claim of inventing the idea that individuals adapt their identities within group settings restates theories already well-explored by Smith and Berg in the late '90s, illustrating a tendency among some in the field to "invent" rather than build on existing knowledge. This practice not only misrepresents the originality of an idea but also contributes to the unnecessary fragmentation of psychological science. We must become more discerning. https://lnkd.in/g3BwXRAF

The excessive creation of new constructs and measures leads to fragmentation, complicating the generation of insights and creating barriers to knowledge transfer. This fragmentation makes it difficult to compare results across experiments, limiting the development of a cohesive understanding of phenomena and impeding progress.

To address the challenges of fragmentation, there needs to be a shift toward greater hashtag#methodologicalrigor. We must improve, reuse, and validate existing constructs and hashtag#measures rather than continuously inventing new ones. This approach would make applying insights effectively in hashtag#decisionmaking processes easier and foster a more standardized and accessible body of knowledge.

🎯THERE IS A BETTER WAY
Improve methodological rigor and data quality processes. Apply operational excellence. Leverage data quality and senior stakeholder management to streamline data transformation processes. For example, by identifying and eliminating redundancies in data collection and processing, data-driven decisions' timeliness significantly improves and becomes more accurate.

Key Performance Indicators (KPIs) include efficiency, productivity, and quality outcomes. Focusing on DQ and meta data management and developing or refining KPIs that accurately track the performance of data transformation processes can ensure they align with organizational goals for operational excellence.

🎯WHY PRIOTIZE DQ KPIs?
They ensure accurate, reliable metrics for decision-making. High-quality data underpins effective KPIs, enabling organizations to track performance accurately and make informed strategic decisions, which is essential for operational excellence.

🎯WHY DOES STAKEHOLDER MANAGEMENT MATTER?
It nurtures beneficial relationships between a business and its stakeholders, creating shared value. It helps avoid or resolve conflicts, secure support, communicate effectively, and manage expectations, which is essential for operational excellence.

Emotions are a tool

[ from Neuroscience News ]

Summary: People have more control over how their emotions are influenced by others than previously thought. Researchers found people who wanted to stay calm when presented with upsetting stimuli remained unfazed by angry emotions expressed by others. However, when they wanted to feel angry, they were more highly influenced by others who were angry.

Source: Stanford

Photo Credit: Neuroscience News

Photo Credit: Neuroscience News

In a new study, Stanford psychologists examined why some people respond differently to an upsetting situation and learned that people’s motivations play an important role in how they react.

Their study found that when a person wanted to stay calm, they remained relatively unfazed by angry people, but if they wanted to feel angry, then they were highly influenced by angry people. The researchers also discovered that people who wanted to feel angry also got more emotional when they learned that other people were just as upset as they were, according to the results from a series of laboratory experiments the researchers conducted.

Their findings, published June 13 in Journal of Experimental Psychology: General, reveal that people have more control over how their emotions get influenced than previously realized, the researchers said.

“We have long known that people often try to regulate their emotions when they believe that they are unhelpful,” said James Gross, a professor of psychology at Stanford’s School of Humanities and Sciences. “This set of studies extends this insight by showing that people can also regulate the way they are influenced by others’ emotions.”

….

Researchers have largely assumed that people’s emotions get influenced automatically – in an unconscious, immediate response to other people’s emotions, said Goldenberg. His team’s new research challenges that perspective, he said.

“Our emotions are not passive nor automatic,” Goldenberg said. “They are a little bit of a tool. We have the ability to use our emotions to achieve certain goals. We express certain emotions to convince other people to join our collective cause. On social media, we use emotions to signal to other people that we care about the issues of a group to make sure people know we’re a part of it.”

Further research needs to be done in order to understand the relationship between people and their emotions. One of the next topics Goldenberg says he wants to examine further is whether the desire of people to want to see and experience certain emotions around them lies at the core of how they choose their network of friends and other people around them.

“It seems that the best way to regulate your emotions is to start with the selection of your environment,” Goldenberg said. “If you don’t want to be angry today, one way to do that is to avoid angry people. Do some people have an ingrained preference for stronger emotions than others? That’s one of my next questions.”

Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.

Fundamentals of workplace automation

[ From McKinsey ]

As the automation of physical and knowledge work advances, many jobs will be redefined rather than eliminated—at least in the short term.

 
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The potential of artificial intelligence and advanced robotics to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by the likes of IBM’s Watson, Rethink Robotics’ Baxter, DeepMind, or Google’s driverless car. Just head to an airport: automated check-in kiosks now dominate many airlines’ ticketing areas. Pilots actively steer aircraft for just three to seven minutes of many flights, with autopilot guiding the rest of the journey. Passport-control processes at some airports can place more emphasis on scanning document bar codes than on observing incoming passengers.

What will be the impact of automation efforts like these, multiplied many times across different sectors of the economy? Can we look forward to vast improvements in productivity, freedom from boring work, and improved quality of life? Should we fear threats to jobs, disruptions to organizations, and strains on the social fabric?

Earlier this year, we launched research to explore these questions and investigate the potential that automation technologies hold for jobs, organizations, and the future of work.3 Our results to date suggest, first and foremost, that a focus on occupations is misleading. Very few occupations will be automated in their entirety in the near or medium term. Rather, certain activities are more likely to be automated, requiring entire business processes to be transformed, and jobs performed by people to be redefined, much like the bank teller’s job was redefined with the advent of ATMs.

More specifically, our research suggests that as many as 45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies.4 In the United States, these activities represent about $2 trillion in annual wages. Although we often think of automation primarily affecting low-skill, low-wage roles, we discovered that even the highest-paid occupations in the economy, such as financial managers, physicians, and senior executives, including CEOs, have a significant amount of activity that can be automated.

The organizational and leadership implications are enormous: leaders from the C-suite to the front line will need to redefine jobs and processes so that their organizations can take advantage of the automation potential that is distributed across them. And the opportunities extend far beyond labor savings. When we modeled the potential of automation to transform business processes across several industries, we found that the benefits (ranging from increased output to higher quality and improved reliability, as well as the potential to perform some tasks at superhuman levels) typically are between three and ten times the cost. The magnitude of those benefits suggests that the ability to staff, manage, and lead increasingly automated organizations will become an important competitive differentiator.

Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.

AI helps brewers predict new beer varieties

Craftsmanship refers to something made with the highest quality. It requires a distinct mindset and approach. Values like durability, integrity, and calling are often associated with craftsmanship. 

In this story, AI enhances the notion of craft for a Carlsberg  brewing team, extending capabilities that have been practiced for centuries. 

Read More

US study of diversity being valued versus considered

[ from The Pew Research Center ] Three-quarters of Americans agree it is important for workplaces to promote racial and ethnic diversity, according to a study published by the Pew Research Center today.

The response doesn’t vary too much by race, with 81% of black Americans saying it is very or somewhat important, 73% of whites, and 75% of Hispanics. Yet while it appears that most Americans support diversity, the Pew study suggests the support doesn’t actually extend to action to ensure that it increases.

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Just 24% of Americans said a person’s race or ethnicity should be taken into account alongside their qualifications in hiring decisions in order to increase diversity. Nearly three-quarters said only an applicant’s qualifications should be considered in hiring—even if it meant less diversity.

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On this, a racial divide emerges: 78% of white Americans believe only qualifications should count, compared to 54% of black Americans. More than two-thirds of Hispanics also said only qualifications should count.

This disconnect can be seen at Microsoft, the world’s most valuable company. It has a compensation plan for executives linked to diverse hiring, but some employees took to an internal message board to denounce it as discriminatory, Quartz found. “As long as we give more money and higher annual reviews explicitly for NOT hiring/promoting white men and Asians, this will continue to be a serious problem at the company,” one comment read.

The wider implication of the Pew study is that most Americans believe achievement in their education system and the labor market is sufficiently based on merit. That’s despite evidence to the contrary.

An analysis by the New York Times in 2017 found that black and Hispanic students were more underrepresented at top colleges and universities in the US than they were 35 years earlier, even after decades of affirmative action. The roots of the problem extend to an inequitable and segregated school system. A report by the US Department of Education in 2014 found that schools with lots of students of color tended to have less access to advanced courses (pdf) such as AP subjects, fewer experienced teachers, and limited access to resources needed to provide a high quality education.

Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.

Skills have a “half-life” - it's 5 years, and quickly shortening

[ from Desire2Learn ]

As technology and automation continue to change the meaning of work and the skills required of the workforce, our education systems need to adapt and require action and support from governments.

Key Findings:

  • Job skills are becoming outdated more rapidly, lasting only 1 to 5 years.

  • Given the unknown nature of future jobs and their job skill requirements, soft skills are the durable skills of the future.

  • Durable skills are increasingly valued by employers for resilient and adaptable employees who can operate in a global economy.

Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.

The Future of Jobs report 2018

[ From the Centre for the New Economy and Society ]

As technological breakthroughs rapidly shift the frontier between the work tasks performed by humans and those performed by machines and algorithms, global labour markets are undergoing major transformations. These transformations, if managed wisely, could lead to a new age of good work, good jobs and improved quality of life for all, but if managed poorly, pose the risk of widening skills gaps, greater inequality and broader polarization.

As the Fourth Industrial Revolution unfolds, companies are seeking to harness new and emerging technologies to reach higher levels of efficiency of production and consumption, expand into new markets, and compete on new products for a global consumer base composed increasingly of digital natives. Yet in order to harness the transformative potential of the Fourth Industrial Revolution, business leaders across all industries and regions will increasingly be called upon to formulate a comprehensive workforce strategy ready to meet the challenges of this new era of accelerating change and innovation.

This report finds that as workforce transformations accelerate, the window of opportunity for proactive management of this change is closing fast and business, government and workers must proactively plan and implement a new vision for the global labor market. The report’s key findings include:

• Drivers of change: Four specific technological advances—ubiquitous high-speed mobile internet; artificial intelligence; widespread adoption of big data analytics; and cloud technology—are set to dominate the 2018–2022 period as drivers positively affecting business growth. They are flanked by a range of socio-economic trends driving business opportunities in tandem with the spread of new technologies, such as national economic growth trajectories; expansion of education and the middle classes, in particular in developing economies; and the move towards a greener global economy through advances in new energy technologies.

• Accelerated technology adoption: By 2022, according to the stated investment intentions of companies surveyed for this report, 85% of respondents are likely or very likely to have expanded their adoption of user and entity big data analytics. Similarly, large proportions of companies are likely or very likely to have expanded their adoption of technologies such as the internet of things and app- and webenabled markets, and to make extensive use of cloud computing. Machine learning and augmented and virtual reality are poised to likewise receive considerable business investment.

• Trends in robotization: While estimated use cases for humanoid robots appear to remain somewhat more limited over the 2018–2022 period under consideration in this report, collectively, a broader range of recent robotics technologies at or near commercialization— including stationary robots, non-humanoid land robots and fully automated aerial drones, in addition to machine learning algorithms and artificial intelligence— are attracting significant business interest in adoption. Robot adoption rates diverge significantly across sectors, with 37% to 23% of companies planning this investment, depending on industry. Companies across all sectors are most likely to adopt the use of stationary robots, in contrast to humanoid, aerial or underwater robots, however leaders in the Oil & Gas industry report the same level of demand for stationary and aerial and underwater robots, while employers in the Financial Services industry are most likely to signal the planned adoption of humanoid robots in the period up to 2022.

• Changing geography of production, distribution and value chains: By 2022, 59% of employers surveyed for this report expect that they will have significantly modified how they produce and distribute by changing the composition of their value chain and nearly half expect to have modified their geographical base of operations. When determining job location decisions, companies overwhelmingly prioritize the availability of skilled local talent as their foremost consideration, with 74% of respondents providing this factor as their key consideration. In contrast, 64% of companies cite labour costs as their main concern. A range of additional relevant factors—such as the flexibility of local labour laws, industry agglomeration effects or proximity of raw materials—were considered of lower importance.

• Changing employment types: Nearly 50% of companies expect that automation will lead to some reduction in their full-time workforce by 2022, based on the job profiles of their employee base today. However, 38% of businesses surveyed expect to extend their workforce to new productivity-enhancing roles, and more than a quarter expect automation to lead to the creation of new roles in their enterprise. In addition, businesses are set to expand their use of contractors doing task-specialized work, with many respondents highlighting their intention to engage workers in a more flexible manner, utilizing remote staffing beyond physical offices and decentralization of operations.

• A new human-machine frontier within existing tasks: Companies expect a significant shift on the frontier between humans and machines when it comes to existing work tasks between 2018 and 2022. In 2018, an average of 71% of total task hours across the 12 industries covered in the report are performed by humans, compared to 29% by machines. By 2022 this average is expected to have shifted to 58% task hours performed by humans and 42% by machines. In 2018, in terms of total working hours, no work task was yet estimated to be predominantly performed by a machine or an algorithm. By 2022, this picture is projected to have somewhat changed, with machines and algorithms on average increasing their contribution to specific tasks by 57%. For example, by 2022, 62% of organization’s information and data processing and information search and transmission tasks will be performed by machines compared to 46% today. Even those work tasks that have thus far remained overwhelmingly human—communicating and interacting (23%); coordinating, developing, managing and advising (20%); as well as reasoning and decisionmaking (18%)—will begin to be automated (30%, 29%, and 27% respectively). Relative to their starting point today, the expansion of machines’ share of work task performance is particularly marked in the reasoning and decision-making, administering, and looking for and receiving job-related information tasks.

• A net positive outlook for jobs: However this finding is tempered by optimistic estimates around emerging tasks and growing jobs which are expected to offset declining jobs. Across all industries, by 2022, growth in emerging professions is set to increase their share of employment from 16% to 27% (11% growth) of the total employee base of company respondents, whereas the employment share of declining roles is set to decrease from currently 31% to 21% (10% decline). About half of today’s core jobs—making up the bulk of employment across industries—will remain stable in the period up to 2022. Within the set of companies surveyed, representing over 15 million workers in total, current estimates would suggest a decline of 0.98 million jobs and a gain of 1.74 million jobs. Extrapolating these trends across those employed by large firms in the global (nonagricultural) workforce, we generate a range of estimates for job churn in the period up to 2022. One set of estimates indicates that 75 million jobs may be displaced by a shift in the division of labour between humans and machines, while 133 million new roles may emerge that are more adapted to the new division of labour between humans, machines and algorithms. While these estimates and the assumptions behind them should be treated with caution, not least because they represent a subset of employment globally, they are useful in highlighting the types of adaptation strategies that must be put in place to facilitate the transition of the workforce to the new world of work. They represent two parallel and interconnected fronts of change in workforce transformations: 1) large-scale decline in some roles as tasks within these roles become automated or redundant, and 2) large-scale growth in new products and services—and associated new tasks and jobs— generated by the adoption of new technologies and other socio-economic developments such as the rise of middle classes in emerging economies and demographic shifts.

• Emerging in-demand roles: Among the range of established roles that are set to experience increasing demand in the period up to 2022 are Data Analysts and Scientists, Software and Applications Developers, and Ecommerce and Social Media Specialists, roles that are significantly based on and enhanced by the use of technology. Also expected to grow are roles that leverage distinctively ‘human' skills, such as Customer Service Workers, Sales and Marketing Professionals, Training and Development, People and Culture, and Organizational Development Specialists as well as Innovation Managers. Moreover, our analysis finds extensive evidence of accelerating demand for a variety of wholly new specialist roles related to understanding and leveraging the latest emerging technologies: AI and Machine Learning Specialists, Big Data Specialists, Process Automation Experts, Information Security Analysts, User Experience and Human-Machine Interaction Designers, Robotics Engineers, and Blockchain Specialists.

• Growing skills instability: Given the wave of new technologies and trends disrupting business models and the changing division of labour between workers and machines transforming current job profiles, the vast majority of employers surveyed for this report expect that, by 2022, the skills required to perform most jobs will have shifted significantly. Global average skills stability—the proportion of core skills required to perform a job that will remain the same—is expected to be about 58%, meaning an average shift of 42% in required workforce skills over the 2018–2022 period.

• A reskilling imperative: By 2022, no less than 54% of all employees will require significant re- and upskilling. Of these, about 35% are expected to require additional training of up to six months, 9% will require reskilling lasting six to 12 months, while 10% will require additional skills training of more than a year. Skills continuing to grow in prominence by 2022 include analytical thinking and innovation as well as active learning and learning strategies. Sharply increasing importance of skills such as technology design and programming highlights the growing demand for various forms of technology competency identified by employers surveyed for this report. Proficiency in new technologies is only one part of the 2022 skills equation, however, as ‘human’ skills such as creativity, originality and initiative, critical thinking, persuasion and negotiation will likewise retain or increase their value, as will attention to detail, resilience, flexibility and complex problem-solving. Emotional intelligence, leadership and social influence as well as service orientation also see an outsized increase in demand relative to their current prominence.

• Current strategies for addressing skills gaps: Companies highlight three future strategies to manage the skills gaps widened by the adoption of new technologies. They expect to hire wholly new permanent staff already possessing skills relevant to new technologies; seek to automate the work tasks concerned completely; and retrain existing employees. The likelihood of hiring new permanent staff with relevant skills is nearly twice the likelihood of strategic redundancies of staff lagging behind in new skills adoption. However, nearly a quarter of companies are undecided or unlikely to pursue the retraining of existing employees, and two-thirds expect workers to adapt and pick up skills in the course of their changing jobs. Between one-half and two-thirds are likely to turn to external contractors, temporary staff and freelancers to address their skills gaps.

• Insufficient reskilling and upskilling: Employers indicate that they are set to prioritize and focus their re- and upskilling efforts on employees currently performing high-value roles as a way of strengthening their enterprise’s strategic capacity, with 54% and 53% of companies, respectively, stating they intend to target employees in key roles and in frontline roles which will be using relevant new technologies. In addition, 41% of employers are set to focus their reskilling provision on high-performing employees while a much smaller proportion of 33% stated that they would prioritize at-risk employees in roles expected to be most affected by technological disruption. In other words, those most in need of reskilling and upskilling are least likely to receive such training.

There are complex feedback loops between new technology, jobs and skills. New technologies can drive business growth, job creation and demand for specialist skills but they can also displace entire roles when certain tasks become obsolete or automated. Skills gaps—both among workers and among the leadership of organizations—can speed up the trends towards automation in some cases but can also pose barriers to the adoption of new technologies and therefore impede business growth.

The findings of this report suggest the need for a comprehensive ‘augmentation strategy’, an approach where businesses look to utilize the automation of some job tasks to complement and enhance their human workforces’ comparative strengths and ultimately to enable and empower employees to extend to their full potential. Rather than narrowly focusing on automation-based labour cost savings, an augmentation strategy takes into account the broader horizon of value-creating activities that can be accomplished by human workers, often in complement to technology, when they are freed of the need to perform routinized, repetitive tasks and better able to use their distinctively human talents.

However, to unlock this positive vision, workers will need to have the appropriate skills enabling them to thrive in the workplace of the future and the ability to continue to retrain throughout their lives. Crafting a sound in-company lifelong learning system, investing in human capital and collaborating with other stakeholders on workforce strategy should thus be key business imperatives, critical to companies’ medium to long-term growth, as well as an important contribution to society and social stability. A mindset of agile learning will also be needed on the part of workers as they shift from the routines and limits of today’s jobs to new, previously unimagined futures. Finally, policy-makers, regulators and educators will need to play a fundamental role in helping those who are displaced repurpose their skills or retrain to acquire new skills and to invest heavily in the development of new agile learners in future workforces by tackling improvements to education and training systems, as well as updating labour policy to match the realities of the Fourth Industrial Revolution.

Christine Haskell, PHD has built her practice on credible, published research and data. In the Research Series, you’ll find highlights, shareable statistics, and links to the full source material.