IPPR Report Finds "Women Twice As Vulnerable To Automation," Omits Value Of Human Interaction - 9 minutes read
IPPR Report Finds "Women Twice As Vulnerable To Automation," Omits Value Of Human Interaction
A recent report from theInstitute for Public Policy Research(IPPR) found that women are twice as vulnerable to automation by robots as men, due to the jobs at risk of automation that are overrepresented by women. However, it is debatable whether certain job categories included inthe reportas being at a high risk of automation, are likely to be fully automated anytime soon. So is this report painting an overly bleak picture about the future of work for women?
The report also states that there must be a focus on ensuring that new roles enabled by automation are made accessible to women and black and minority ethnic groups (BAMEs), otherwise automation (as with any new technology) will only benefit those currently in positions of power. While this is indeed the case, women may actually bebetter suited to these new roles that require high emotional intelligenceand interpersonal skills, and could better complement the process-driven reasoning of AI than men.
Whether or not women and men will be affected by automation differently, this article series will respond to the assumptions of the report and put them in a more nuanced context. In Part two we will hear more from Jacqueline de Rojas CBE, the President oftechUKand chair ofDigital Leaders, whom I met at London Tech Week, to discuss the wider implications of the report and what the future holds for women in a digital world.
Historically, if not working in the same brutal conditions as their male counterparts or being left with the housework,women have worked in roles that were seen to fit with their nature—usually complex and service-oriented jobs like midwifery, clerical work or operating telephone switchboards. It seems the paradigms of male and female jobs still exist today, but the IPPR report that puts women at a greater risk of automation than men may be underestimating the intricacies of work dominated by women. The key statistic from the report is that 9% of women are employed in roles with a high potential for automation by robots, compared with 4% of men, and are therefore twice as vulnerable to automation by robots as men overall. Certain roles certainly employ a higher proportion of women than men (as shown in Tables 1.1 and 1.2 from the report, below), but the report assumes a comprehensive level of automation that does not practically exist yet in a variety of roles. While pointing out that automation “depends not just on technological potential, but on social and economic factors too” such as whether automation will be cheaper than human labor, the report still overestimates the technical capacity of robots to take over intricate and nuanced tasks.
Service industries like cleaning and waiting tables have higher proportions of women than men, but these roles involve incredibly dextrous tasks that are not suitable for robots to take over any time soon. The professions highlighted above, for example, involve applying a similar process to any number of scenarios (different houses and furnishings, demanding customers, incredibly busy periods) which require a depth of knowledge and contextual experience that machines can not currently apply in real-time—let alone provide a positive customer experience while doing it. The report itself includes this caveat: “there are ‘engineering bottlenecks’, which mean the features of jobs that are in many ways most ‘human’–like emotional intelligence, creativity, and perception and manipulation in unstructured situations–cannot currently be automated.” In fact, roles like farm workers, packers, bottles and canners, and shelf fillers are all at much higher risk of automation as they involve a singular task, and have more than twice the proportion of men working in those positions than women (as shown in Table 1.1).
Even the most advanced AI systems find it difficult to extrapolate outside a limited range as humans do—for instance tolink touch and visiona system must be trained on millions of images and the corresponding tactile information—and the roles outlined as at high risk of automation, with a high proportion of female workers, all require a dexterity that robots are not likely to achieve in the near future. De Rojas points out, however, that the likely scenario of partial automation may “free up women to focus on other tasks and also offer increased flexibility, which could be very beneficial for working women,” and indeed this collaboration between human and machine will open up more opportunities for the workforce as a whole.
The second part of the report focuses on ways in which inequality through automation might be avoided. The authors offer four proposals as to how new roles may be made more available to women and BAME people as labor-intensive roles are automated, and more thought-based, management roles emerge for humans to move into. Stating that “the impact [of automation] depends on who is able to access the new jobs, what happens to pay and conditions... and how the ‘plenty’ created by higher productivity is distributed,” the report clearly points out that for automation to work for everyone, women and BAME people must be considered before automation becomes widespread. Again, the report makes a false assumption however: that women will continue to be disadvantaged once more emotionally intelligent roles appear. On the contrary,research from Korn Ferry in 2016found that women performed consistently better than men in 11 of 12 emotional intelligence competencies that are strongly associated with strong leadership skills, including coaching and mentoring, inspirational leadership and conflict management. This may well translate to better management skills once the vast majority of analytical thinking is completed by AI and interpersonal relationships become the dominant business currency.
A recent shift towards more women on boards, more female business leaders andmore women founding companiesdoes not show signs of slowing, or of being brought back to the former patriarchal status quo. With the highest ever amount offemale CEOs on the Fortune 500 list, there is not much reason to think that women would be disproportionately disadvantaged by a move towards more management-focused roles and those that require putting the work of robots into a nuanced context. Granted, the question of “how plenty is distributed” remains, as the current paradigm of men holding corporate power would need to be sufficiently addressed to avoid an adverse impact on women (as the report points out) but in a digital age where anybody can start their own company, who is to say that women won’t outcompete the old boys club? Preparing for a situation where everyone has an equal chance in the automated future is crucial, de Rojas points out, and “with the right policy actions by governments and businesses, women could benefit from the mix of sectors, skills, and occupations that will become important as technology adoption advances.” This outcome is entirely possible, and in everyone’s interests, but we must take steps to guide automation in this direction before our fate is decided for us.
Automation will certainly affect women and men differently—as much as we are moving towards a fair and balanced society,we are more likely to achieve widespread automation before complete gender parity. But that women are more at risk of being displaced, as the IPPR report suggests, is not necessarily the case. I would argue instead that women are better placed to take up managerial and more emotionally intelligent roles once robots take over process-driven work (like thoseroles currently dominated by men), assuming that opportunities are made equally available to all.
The report is a necessary and useful comment on how automation will impact the workplace, however, as it makes clear there is a need to steer automation in the right direction for the common good, rather than allowing current paradigms to dictate how we move forward. Whether women are as at risk as the IPPR report suggests, or whether they need any help to move into leadership roles which they may be better at than men, remains to be seen.
In part two, Jacqueline de Rojas will discuss the wider implications of automation for women, and what we must do now to prepare for a future that works for everyone.
Source: Forbes.com
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Keywords:
Institute for Public Policy Research • Woman • Vulnerability • Automation • Value (ethics) • Interpersonal relationship • Public policy • Research • Institute for Public Policy Research • Vulnerability • Automation • Robotics • Employment • Automation • Employment • Automation • Employment • Automation • Woman • Demography of the United Kingdom • Minority group • Automation • Technology • Power (social and political) • Case law • Woman • Emotion • Social skills • Scientific method • Reason • Artificial intelligence • Automation • Order of the British Empire • Technical week • Woman • Nature • Midwifery • Telephone • Employment • Institute for Public Policy Research • Woman • Risk • Automation • Employment • Statistics • Automation • Robotics • Automation • Robot • Automation • Automation • Technology • Social science • Automation • Human • Labour economics • Technology • Robot • Time • Scientific method • Number • Knowledge • Machine • Employment • Emotional intelligence • Creativity • Perception • Psychological manipulation • Automation • Artificial intelligence • System • Human • Somatosensory system • System • Mental image • Somatosensory system • Information • Risk • Automation • Robot • Automation • Workforce • Economic inequality • Automation • Person • Management • Automation • Employment • Employment contract • Productivity • Automation • Human trafficking • Automation • Emotional intelligence • Scientific method • Korn Ferry • Emotional intelligence • Competence (human resources) • Leadership • Coaching • Mentorship • Conflict management • Management • Artificial intelligence • Interpersonal relationship • Business • Woman • Woman • Business • Leadership • Woman • Patriarchy • Status quo • Wealth • Reason • Management • Employment • Robotics • Paradigm • Information Age • Automation • Future • Rights • Policy • Social actions • Government • Business • Skill • Employment • Technology • Automation • Automation • Gender • Purchasing power parity • Institute for Public Policy Research • Management • Robotics • Employment • Equal opportunity • Automation • Employment • Automation • Common good • Institute for Public Policy Research • Automation •
A recent report from theInstitute for Public Policy Research(IPPR) found that women are twice as vulnerable to automation by robots as men, due to the jobs at risk of automation that are overrepresented by women. However, it is debatable whether certain job categories included inthe reportas being at a high risk of automation, are likely to be fully automated anytime soon. So is this report painting an overly bleak picture about the future of work for women?
The report also states that there must be a focus on ensuring that new roles enabled by automation are made accessible to women and black and minority ethnic groups (BAMEs), otherwise automation (as with any new technology) will only benefit those currently in positions of power. While this is indeed the case, women may actually bebetter suited to these new roles that require high emotional intelligenceand interpersonal skills, and could better complement the process-driven reasoning of AI than men.
Whether or not women and men will be affected by automation differently, this article series will respond to the assumptions of the report and put them in a more nuanced context. In Part two we will hear more from Jacqueline de Rojas CBE, the President oftechUKand chair ofDigital Leaders, whom I met at London Tech Week, to discuss the wider implications of the report and what the future holds for women in a digital world.
Historically, if not working in the same brutal conditions as their male counterparts or being left with the housework,women have worked in roles that were seen to fit with their nature—usually complex and service-oriented jobs like midwifery, clerical work or operating telephone switchboards. It seems the paradigms of male and female jobs still exist today, but the IPPR report that puts women at a greater risk of automation than men may be underestimating the intricacies of work dominated by women. The key statistic from the report is that 9% of women are employed in roles with a high potential for automation by robots, compared with 4% of men, and are therefore twice as vulnerable to automation by robots as men overall. Certain roles certainly employ a higher proportion of women than men (as shown in Tables 1.1 and 1.2 from the report, below), but the report assumes a comprehensive level of automation that does not practically exist yet in a variety of roles. While pointing out that automation “depends not just on technological potential, but on social and economic factors too” such as whether automation will be cheaper than human labor, the report still overestimates the technical capacity of robots to take over intricate and nuanced tasks.
Service industries like cleaning and waiting tables have higher proportions of women than men, but these roles involve incredibly dextrous tasks that are not suitable for robots to take over any time soon. The professions highlighted above, for example, involve applying a similar process to any number of scenarios (different houses and furnishings, demanding customers, incredibly busy periods) which require a depth of knowledge and contextual experience that machines can not currently apply in real-time—let alone provide a positive customer experience while doing it. The report itself includes this caveat: “there are ‘engineering bottlenecks’, which mean the features of jobs that are in many ways most ‘human’–like emotional intelligence, creativity, and perception and manipulation in unstructured situations–cannot currently be automated.” In fact, roles like farm workers, packers, bottles and canners, and shelf fillers are all at much higher risk of automation as they involve a singular task, and have more than twice the proportion of men working in those positions than women (as shown in Table 1.1).
Even the most advanced AI systems find it difficult to extrapolate outside a limited range as humans do—for instance tolink touch and visiona system must be trained on millions of images and the corresponding tactile information—and the roles outlined as at high risk of automation, with a high proportion of female workers, all require a dexterity that robots are not likely to achieve in the near future. De Rojas points out, however, that the likely scenario of partial automation may “free up women to focus on other tasks and also offer increased flexibility, which could be very beneficial for working women,” and indeed this collaboration between human and machine will open up more opportunities for the workforce as a whole.
The second part of the report focuses on ways in which inequality through automation might be avoided. The authors offer four proposals as to how new roles may be made more available to women and BAME people as labor-intensive roles are automated, and more thought-based, management roles emerge for humans to move into. Stating that “the impact [of automation] depends on who is able to access the new jobs, what happens to pay and conditions... and how the ‘plenty’ created by higher productivity is distributed,” the report clearly points out that for automation to work for everyone, women and BAME people must be considered before automation becomes widespread. Again, the report makes a false assumption however: that women will continue to be disadvantaged once more emotionally intelligent roles appear. On the contrary,research from Korn Ferry in 2016found that women performed consistently better than men in 11 of 12 emotional intelligence competencies that are strongly associated with strong leadership skills, including coaching and mentoring, inspirational leadership and conflict management. This may well translate to better management skills once the vast majority of analytical thinking is completed by AI and interpersonal relationships become the dominant business currency.
A recent shift towards more women on boards, more female business leaders andmore women founding companiesdoes not show signs of slowing, or of being brought back to the former patriarchal status quo. With the highest ever amount offemale CEOs on the Fortune 500 list, there is not much reason to think that women would be disproportionately disadvantaged by a move towards more management-focused roles and those that require putting the work of robots into a nuanced context. Granted, the question of “how plenty is distributed” remains, as the current paradigm of men holding corporate power would need to be sufficiently addressed to avoid an adverse impact on women (as the report points out) but in a digital age where anybody can start their own company, who is to say that women won’t outcompete the old boys club? Preparing for a situation where everyone has an equal chance in the automated future is crucial, de Rojas points out, and “with the right policy actions by governments and businesses, women could benefit from the mix of sectors, skills, and occupations that will become important as technology adoption advances.” This outcome is entirely possible, and in everyone’s interests, but we must take steps to guide automation in this direction before our fate is decided for us.
Automation will certainly affect women and men differently—as much as we are moving towards a fair and balanced society,we are more likely to achieve widespread automation before complete gender parity. But that women are more at risk of being displaced, as the IPPR report suggests, is not necessarily the case. I would argue instead that women are better placed to take up managerial and more emotionally intelligent roles once robots take over process-driven work (like thoseroles currently dominated by men), assuming that opportunities are made equally available to all.
The report is a necessary and useful comment on how automation will impact the workplace, however, as it makes clear there is a need to steer automation in the right direction for the common good, rather than allowing current paradigms to dictate how we move forward. Whether women are as at risk as the IPPR report suggests, or whether they need any help to move into leadership roles which they may be better at than men, remains to be seen.
In part two, Jacqueline de Rojas will discuss the wider implications of automation for women, and what we must do now to prepare for a future that works for everyone.
Source: Forbes.com
Powered by NewsAPI.org
Keywords:
Institute for Public Policy Research • Woman • Vulnerability • Automation • Value (ethics) • Interpersonal relationship • Public policy • Research • Institute for Public Policy Research • Vulnerability • Automation • Robotics • Employment • Automation • Employment • Automation • Employment • Automation • Woman • Demography of the United Kingdom • Minority group • Automation • Technology • Power (social and political) • Case law • Woman • Emotion • Social skills • Scientific method • Reason • Artificial intelligence • Automation • Order of the British Empire • Technical week • Woman • Nature • Midwifery • Telephone • Employment • Institute for Public Policy Research • Woman • Risk • Automation • Employment • Statistics • Automation • Robotics • Automation • Robot • Automation • Automation • Technology • Social science • Automation • Human • Labour economics • Technology • Robot • Time • Scientific method • Number • Knowledge • Machine • Employment • Emotional intelligence • Creativity • Perception • Psychological manipulation • Automation • Artificial intelligence • System • Human • Somatosensory system • System • Mental image • Somatosensory system • Information • Risk • Automation • Robot • Automation • Workforce • Economic inequality • Automation • Person • Management • Automation • Employment • Employment contract • Productivity • Automation • Human trafficking • Automation • Emotional intelligence • Scientific method • Korn Ferry • Emotional intelligence • Competence (human resources) • Leadership • Coaching • Mentorship • Conflict management • Management • Artificial intelligence • Interpersonal relationship • Business • Woman • Woman • Business • Leadership • Woman • Patriarchy • Status quo • Wealth • Reason • Management • Employment • Robotics • Paradigm • Information Age • Automation • Future • Rights • Policy • Social actions • Government • Business • Skill • Employment • Technology • Automation • Automation • Gender • Purchasing power parity • Institute for Public Policy Research • Management • Robotics • Employment • Equal opportunity • Automation • Employment • Automation • Common good • Institute for Public Policy Research • Automation •