Last week I had the opportunity to read your opinion piece, We need to have a conversation-about race from the July 1st paper. As the title suggests, I would like to continue the conversation. Thank you for sharing your thoughts with the Wenatchee Valley on your perspective regarding racism in the past and with current events. As mindful readers often do, I read your article a few times thinking about the overall message you wanted your readers to take away, the reasoning supporting your claims, and some wonderings that have stayed with me.

You mentioned the Rev. James David Manning and quoted him, Black people have to knock that chip off their shouldernobody can say anything about Black people publicly without being called a racist and a bigot. My first wondering was about your relationship with Rev. Manning. I was curious to know more about him so I did some research and found many articles, including one from the Huff Post. He sounds like a very involved Black man within his church, school, and society. How long have you known Rev. Manning? Was the quote you shared from a personal conversation you had with him regarding race? I thought it was interesting to read about some of his other opinions, including education. I wonder why you didnt share with your readers his involvement with his school and locking up students, teaching kids to hate gay people, and convincing parents to abandon their children? While these topics dont necessarily have to do with race, I do think it is important that one voice does not speak to the narrative for all. As a white woman, I am not a representative of all white people. Likewise, the Rev. James David Manning is not the one voice for all Black people.

I am also curious about your claim that Black people create problems by their own bad behavior. What do you define as bad behavior? Everyone exhibits bad behavior from time to time. Yet, why is it that as a white person, if I am pulled over by the police (which has happened a few times) I am always given a chance to speak, ask for clarification, or admit to my bad behavior without fear? Why does being Black mean one must Allow the arresting officers to take them into custody peacefully even if they have not committed any crime?

You mentioned that in present society, Black people are no longer being shut out of equal opportunities by referencing the West Point graduation and how every race and gender were represented. Yet you did not provide any statistics. Graduates of West Point themselves are acknowledging there is systemic racism and havewritten a proposal to the West Point Leadership asking for an antiracist West Point. When I think of this representation, I picture the same number of white graduates and graduates of color. To me, equal representation means equal opportunities. I am curious how stating the graduates represented every race and gender supports the idea that Institutional Racism is no longer relevant? You mentioned that, We honor those who have achieved success through hard work and honesty. How does the comparison of pay for Black and white men with the same experience and education doing the same job in the same geographic location fit into this claim? Black people who work hard and achieve success do not benefit equally.

As a white woman, I know I will never understand what it is like to be a person of color. I can, however, try to educate myself in the uncomfortable concepts such as prejudice, discrimination, racism, and oppression and my part in them. I have read the definition of racism in many sources. In Robin DiAngelos book, What Does it Mean to Be White? she writes, Racism is more than race prejudice. Anyone across any race can have prejudice. But racism is a macro-level social system that whites control and use to the advantage of whites as a group. Thus, all whites are collectively implicated in this system.

I did not choose to be born into a systemic racist society, but I do know I benefit in many ways because I am white. I think it is time to listen to people of color and not dismiss their challenges. How can ones personal experience be misguided? People of color are not thugs or bad boys and girls who are driving this false agenda. They are our fellow doctors, teachers, nurses, baristas, engineers, scientists, architects, UPS drivers, chefs, hair stylists, dentists, construction workers, etc. who have their own stories, narratives, and experiences. Whether I agree with their means of protest or not, it is time for a change in our society. These protests would not be happening if society was indeed equal. In my opinion, the loss of material things is not equal to the loss of lives.

I believe it is important to participate in a dialogue between people where we can listen, learn, and reflect. Sometimes that means accepting discomfort and non-closure. It also means that I may not always agree with what is being shared based on my own experiences. I know my experiences limit me and my understanding. Instead of focusing on the disagreement I listen to try to understand how my ideas, behaviors, or the system is problematic. As a white woman and ally, it is my responsibility to allow my thoughts and ideas to change based on what I learn about the world and the experiences of others.

Thank you for opening the conversation.

Daveen Cordell

Seattle (Former Cashmere High School Graduate

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Continuing the Conversation - Cashmere Valley Record

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Tracy Henderson

FAYETTEVILLE, Ark. University of Arkansas alumna Tracy Henderson of Austin, Texas, says giving back is a great way to leave a legacy. Her planned gift commitment of $300,000 will create three new endowments at the university.

The gift was counted in Campaign Arkansas, the universitys recently concluded capital campaign that raised nearly $1.45 billion to advance academic opportunity.

Hendersons endowments will provide a scholarship for students who were placed in foster care during a portion of or throughout their childhood; funding for the Department of History in the Fulbright College of Arts and Sciences; and support for the University Libraries.

Henderson says one reason she decided to attend the U of A was because her father played football for the Razorbacks. She earned a Bachelor of Arts in history in 1984, minored in French and says she dreamed of working in international management one day. Henderson completed her Master in Public Affairs degree from the Lyndon B. Johnson School of Public Affairs at the University of Texas at Austin and then spent 28 years working with the state of Texas, including time with the legislature, before serving as chief financial officer of the Texas Health and Human Services Commission and later the Texas Department of Family and Protective Services. She now works part-time with the U.S. Treasury as an intermittent advisor.

At this point in my career, I am doing international management, she said, noting that she travels internationally for her job frequently. And its what I set out to do all those years ago at the U of A. I grew up a lot during those four years in Fayetteville and started honing the tools to find myself.

The Tracy L. Henderson Endowed Scholarship: Promoting Foster Care Success was inspired by her work with protective and regulatory services in Texas and a similar scholarship program that is offered to all residents of Texas.

My time as chief financial officer for protective and regulatory services was a learning experience, she said. I have great admiration for people who work in this area. I wanted to be able to help former foster care children whether traditional students or not get a college degree. I was fortunate to graduate debt-free from college, and I want others to be able to do the same.

Scholarship preference will be given to qualified students who were placed in foster care during a portion of or throughout their childhood and who are admitted as full-time students at the university.

I met Tracy through the Austin Chapter of the Arkansas Alumni Association and could see right away that she was a loyal volunteer, said Katy Nelson-Ginder, associate vice chancellor for development. Her passion for the university and the Razorbacks was evident, and she showed great pride for her history degree and her familys U of A legacy.

Through her work with family and protective services, Tracy saw the potential of foster children who had overcome obstacles and wanted to continue their education. She is investing in them with this gift, so theyll have the opportunity to attend college and aspire to their dreams. This just further demonstrates Tracys passion for helping others and her philanthropic spirit.

The Tracy L. Henderson Endowment for History Research and Support will assist undergraduate or graduate-level students in the Department of History, where Henderson earned her bachelors degree.

Funding from the endowment will be used to cover costs related to conducting research, presenting research at conferences and associated travel or conference expenses.

We are so grateful for Tracys support, said Jim Gigantino II, professor and chair of the Department of History. Not only is she helping our fantastic students succeed in their education, but she is an outstanding and inspiring example of what one of our graduates can and has achieved.

Hendersons third endowment, the Tracy L. Henderson University Libraries Endowment, will help purchase, maintain, digitize and facilitate access to materials that support scholarship and research at the university.

I spent a lot of time at Mullins Library as a history major, Henderson said.

University Libraries Dean Dennis Clark said, This endowment enables us to provide students and faculty with the collections and access essential for learning and research.

Henderson is a life member of the Arkansas Alumni Association and is counted as a Thoroughred for her 30 years of consecutive giving to the university. She is also included in the Towers of Old Main, a giving society for the universitys most generous benefactors.

About Campaign Arkansas: Campaign Arkansas is the recently concluded capital campaign for the University of Arkansas that raised a record $1.449 billion to support the universitys academic mission and other key priorities, including academic and need-based scholarships, technology enhancements, new and renovated facilities, undergraduate, graduate and faculty research, study abroad opportunities and other innovative programs. The University of Arkansas provides an internationally competitive education for undergraduate and graduate students in a wide spectrum of disciplines as it works to fulfill its public land-grant mission to serve Arkansas and beyond as a partner, resource and catalyst.

About the University of Arkansas: The University of Arkansas provides an internationally competitive education for undergraduate and graduate students in more than 200 academic programs. The university contributes new knowledge, economic development, basic and applied research, and creative activity while also providing service to academic and professional disciplines. The Carnegie Foundation classifies the University of Arkansas among fewer than 3% of colleges and universities in America that have the highest level of research activity. U.S. News & World Report ranks the University of Arkansas among its top American public research universities. Founded in 1871, the University of Arkansas comprises 10 colleges and schools and maintains a low student-to-faculty ratio that promotes personal attention and close mentoring.

Originally posted here:
Three New Endowments Created Thanks to Henderson's $300000 Gift - University of Arkansas Newswire

Stanford will not allow students who take leaves of absence to participate in or hold leadership positions in voluntary student organizations (VSOs), according to the Universitys Aug. 13 Re-Approaching Stanford newsletter. The decision comes even though most undergraduate education will be delivered remotely due to the COVID-19 pandemic.

The decision to enforce this policy for the 2020-21 academic year marks a reversal of the policys suspension by Stanfords Office of Student Engagement (OSE) during the spring 2020 quarter, when VSO leaders who took leaves of absence were permitted to keep their positions.

Vice Provost for Student Affairs Susie Brubaker-Cole and Vice Provost for Undergraduate Education Sarah Church wrote that only students who are enrolled or on their Flex Terms will be able to continue their involvement in student organizations.

Before the 2020-2021 academic year, students were expected to enroll in autumn, winter and spring quarters, with the summer quarter serving as an optional term. This year, Stanford is expecting undergraduates to enroll in three of the four academic quarters in autumn, winter, spring and summer, with the option of taking one quarter off as a Flex Term, in which students are not enrolled in classes but retain access to university services and resources.

Financial officers of VSOs must be enrolled students, and are not eligible to retain their position if they choose to take a leave of absence or are on their Flex Term because of the level of liability and financial responsibility they carry in that role.

OSE oversees and supports more than 650 registered undergraduate and graduate VSOs. OSEs student organization policy on membership states that student organization members must be currently registered students in good academic standing with the university.

The policy also clarifies that students on leaves of absence or suspension cannot serve as members or leaders and must fully disassociate themselves.

A number of students have expressed concern that the enforcement of this policy in the upcoming remote academic year could be detrimental to student organizations and leaders.

Julia Thompson 21, an undergraduate student majoring in aeronautics and astronautics, said that the policy forces students who may not have the resources to be successful in online classes to not take leaves of absences and enroll remotely. She added that racial injustices, unstable home environments, the impact of COVID-19 and other barriers to academic success may limit many students ability to engage in academic responsibilities.

At Stanford, Thompson holds leadership positions in several VSOs, including the Stanford Student Space Initiative, Fascinate, Applied Cybersecurity, Society for International Affairs at Stanford (SIAS) and Health Education for Lifetime Partnerships.

Thompson, who lives in a rural community, told The Daily she has difficulty connecting to the internet to attend online classes and complete coursework. She noted that it would be nearly impossible for her and her two brothers to engage in online classes at the same time, given the lack of high-speed internet in her home.

Moving elsewhere, Thompson said, would require paying rent, and I would need to take a job or internship for the fall quarter. And to do that, I would need to take a leave of absence.

The Universitys decision, however, requires her to choose between a leave of absence and her leadership positions.

Thompson started a petition on Aug. 13 that calls on President Marc Tessier-Lavigne, Provost Persis Drell and Brubaker-Cole to reconsider [the] decision to ban students from participating in and leading VSOs while on a leave of absence. At the time of publication, the petition had more than 180 signatures, comprised of undergraduate and graduate student leaders and a wide variety of student organizations on campus.

The petition emphasizes that VSOs provide crucial resources, communities, and opportunities for students, and the loss of student leaders who are on a leave of absence will also mean that many smaller or newer organizations will cease to exist.

OSE requires each VSO to have at least three student leaders and at least ten members. The petition claims that without enough enrolled members to continue leading the group, many VSOs will be forced out of existence over the coming year. Since some cultural organizations tend to be smaller in size, many students of color and international students will lose a critical resource and community.

Lily Liu 21, president of SIAS, told The Daily that she signed the petition because she believes that students who take leaves of absence should be able to participate in VSOs, as these organizations can provide critical support to students while away from campus.

Liu said that she is extremely disappointed by the schools lack of adaptability, especially since many students are facing financial difficulties or personal crises that prevent them from enrolling.

The Universitys decision puts Liu and other SIAS leaders in a cruel dilemma: choosing between personal well-being and responsibility.

Senior Director of Student Engagement Snehl Naik shared an Aug. 19 email with The Daily, which he sent to student leaders to clarify the upcoming years policies. In the email, Naik wrote that taking a leave of absence from the university includes taking a leave from most experiences of and related to the university, including involvement as a leader or member with student organizations.

Acknowledging the desire among students to remain connected to the Stanford community during leaves of absence, Naik added that students on leave can still attend public events of VSOs.

Naik told The Daily that his office granted exceptions to this policy during spring 2020 to be flexible and support students in a time of great uncertainty. Exceptions would not continue in the upcoming academic year now that weve had some time to pause and rethink how we approach the upcoming academic year, Naik said.

While the Universitys leave of absence policy is beyond OSEs purview, Naik and Jerald Adamos, assistant dean of students and associate director of the Asian American Activities Center, co-chaired the Phase 2 Student Organizations implementation team, which made recommendations to Vice Provosts Brubaker-Cole and Church on how students can remain engaged during their Flex Term or leave of absence.

According to Naik, the implementation team initially recommended that the University allow VSO financial officers to keep their positions during Flex Terms. The vice provosts steering committee, however, decided the liability and responsibilities these roles held required financial officers to be enrolled students.

The Office of the Vice Provost for Student Affairs did not immediately respond to The Dailys request for comment.

Naik said he was concerned by the assertion that some VSOs will cease to exist because of the leave of absence policy, noting that OSE is currently reviewing membership policies that require a minimum of ten students and developing guidelines to streamline the re-entry of inactive student organizations.

Naik wants Stanford students to know that OSE is here for student engagement, we want student engagement to happen, and we are operating from a framework of kindness and grace.

And if there are ideas, Naik added, please share them with us because we are listening.

Contact Cameron Ehsan at cehsan at stanford.edu.

Read more:
Stanford to bar students on leaves of absence from VSOs despite remote learning - The Stanford Daily

Catching a glimpse of a co-workers baby or pet can help humanize workplaces and make colleagues more understanding and empathetic one positive byproduct of the pandemic-fuelled remote work phenomenon

The COVID-19 lockdown has become synonymous with working from home for many people. While some research has suggested that remote work can be isolating, it also makes the competing priorities that workers are juggling very visible even sometimes literally so due to the popularity of video calls.

This has the potential to unite workers with the feeling that they are in this struggle of balancing work and personal responsibilities together.

Whether its kids or pets that are popping up onscreen during Zoom calls, remote work has caused a relaxation in the traditional rules of professional presentation and resulted in a virtual workplace that is not only more flexible, but also more humane.

My preliminary research on how remote work has impacted professionals at accounting firms across Canada suggests that working from home has important implications for how accountants, or any professional working from home for that matter, communicate their expertise and credibility in a virtual workplace.

My survey of these workers suggests that what it means to behave professionally has changed, and that the pandemic has made clear the necessity of being able to bring ones authentic self to work.

According to a recent survey by Statistics Canada, nearly one-third of businesses report that their employees are working remotely during the pandemic lockdown.

Thats almost twice the level reported before the lockdown began. The survey also found that just over one-quarter of employers said theyre likely to offer more employees the chance to continue remote work once the COVID-19 pandemic has passed, with almost 15 per cent saying they plan to make it mandatory.

The accounting firm workers I interviewed suggested that almost all of their companies will allow employees at all seniority levels to work from home, at least part-time, going forward. Remote work is here to stay, and will likely have a lasting impact on how work is conducted.

Making the personal visible

Working from home provides a birds eye view into the personal lives of our colleagues, clients and even our bosses. With every Zoom call, we find ourselves being allowed into the private spaces of our co-workers in unprecedented ways.

Zoom meetings have made the personal lives of our colleagues visible. Take for instance a British professors now-famous on-air intrusion, when her daughter interrupted her while she was being interviewed by the BBC. But Clare Wenham, a working mother at home with her child, is not the exception but rather the rule during the COVID-19 pandemic.

My research suggests that rather than detracting from how one is perceived professionally, these glimpses into co-workers personal lives can improve workplace interactions.

Seeing a colleagues cat or meeting their child on-screen provides a sense of community that people used to get at work and are now desperately craving. These on-camera interactions allow workers to reconnect or get to know one another in a new way.

They also enable employees to see their colleagues as human beings with competing priorities, and they consequently become more flexible and understanding as work and personal lives overlap. This may mean being more tolerant of a missed deadline or more understanding of an unconventional work schedule.

Workwear increasingly casual

Theres lots of tips available on how to dress when working from home, but my research suggests that since the beginning of the lockdown, workwear has become increasingly casual.

While a minimal level of formality is maintained during video calls with clients, respondents are increasingly casual with their colleagues. Some respondents even report hosting virtual Pyjama Mondays as a fun team-building activity.

The decision to dress more casually is not only a desire for comfort, but also reflects both how employees feel about themselves and how they want others to perceive them.

In the book You Are What You Wear: What Your Clothes Reveal About You, clinical psychologist Jennifer Baumgartner explains that clothes often reflect how you feel about yourself. For harried employees who are juggling multiple personal and professional commitments, being seen in a hoodie and yoga pants illustrates the challenges theyre facing during the pandemic.

But this can be a double-edged sword. Activities like Pyjama Days could undermine perceptions of expertise, maturity and competence.

According to one study on dressing for success:

After just a three-second exposure to pictures of one man in a bespoke suit and one in a suit that is off-the-rack, people judged the man in the bespoke suit more favourably. Experiment participants also rated him as more confident, successful, flexible and a higher earner.

Focus on competence, not presentation

But my respondents suggest that remote work removes the focus from what people are wearing to what they say and what they can do. Remote work provides the opportunity to level the playing field and emphasize talent and expertise over how employees present themselves.

Altogether, my study reveals the potential positive benefits of working from home during a global pandemic.

But will this represent a permanent shift in work attitudes?

While my respondents tell me that their firms are implementing permanent plans to allow all employees to work remotely, I certainly hope that the positive changes Im observing in the workplace continue whether people are at home or in the office.

Erica Pimentel, PhD Candidate in Accounting, Concordia Public Scholar, Concordia University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Link:
COVID-19: Pandemic could have a lasting, positive impact on workplace culture - KitchenerToday.com

AUSTIN, Texas The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the universitys existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.

UT Austin already among the worlds top universities for artificial intelligence is poised to develop entirely new classes of algorithms that will lead to more sophisticated and beneficial AI technologies. The university will lead a larger team of researchers that includes the University of Washington, Wichita State University and Microsoft Research.

This is another important step in our universitys ascension as a world leader in machine learning and tech innovation as a whole, and I am grateful to the National Science Foundation for their profound support, said UT Austin interim President Jay Hartzell. Many of the worlds greatest problems and challenges can be solved with the assistance of artificial intelligence, and its only fitting, given UTs history of accomplishment in this area along with the booming tech sector in Austin, that this new NSF institute be housed right here on the Forty Acres.

UT Austin is simultaneously establishing a permanent base for campuswide machine learning research called the Machine Learning Laboratory. It will house the new AI institute and bring together computer and data scientists, mathematicians, roboticists, engineers and ethicists to meet the institutes research goals while also working collaboratively on other interdisciplinary projects. Computer science professor Adam Klivans, who led the effort to win the NSF AI institute competition, will direct both the new institute and the Machine Learning Lab. Alex Dimakis, associate professor of electrical and computer engineering, will serve as the AI institutes co-director.

Machine learning can be used to predict which of thousands of recently formulated drugs might be most effective as a COVID-19 therapeutic, bypassing exhaustive laboratory trial and error, Klivans said. Modern datasets, however, are often diffuse or noisy and tend to confound current techniques. Our AI institute will dig deep into the foundations of machine learning so that new AI systems will be robust to these challenges.

Additionally, many advanced AI applications are limited by computational constraints. For example, algorithms designed to help machines recognize, categorize and label images cant keep up with the massive amount of video data that people upload to the internet every day, and advances in this field could have implications across multiple industries.

Dimakis notes that algorithms will be designed to train video models efficiently. For example, Facebook, one of the AI institutes industry partners, is interested in using these algorithms to make its platform more accessible to people with visual impairments. And in a partnership with Dell Medical School, AI institute researchers will test these algorithms to expedite turnaround time for medical imaging diagnostics, possibly reducing the time it takes for patients to get critical assessments and treatment.

The NSF is investing more than $100 million in five new AI institutes nationwide, including the $20 million project based at UT Austin to advance the foundations of machine learning.

In addition to Facebook, Netflix, YouTube, Dell Technologies and the city of Austin have signed on to transfer this research into practice.

The institute will also pursue the creation of an online masters degree in AI, along with undergraduate research programming and online AI courses for high schoolers and working professionals.

Austin-based tech entrepreneurs Zaib and Amir Husain, both UT Austin alumni, are supporting the new Machine Learning Laboratory with a generous donation to sustain its long-term mission.

The universitys strengths in computer science, engineering, public policy, business and law can help drive applications of AI, Amir Husain said. And Austins booming tech scene is destined to be a major driver for the local and national economy for decades to come.

The Machine Learning Laboratory is based in the Department of Computer Science and is a collaboration among faculty, researchers and students from across the university, including Texas Computing; Texas Robotics; the Department of Statistics and Data Sciences; the Department of Mathematics; the Department of Electrical and Computer Engineering; the Department of Information, Risk & Operations Management; the School of Information; the Good Systems AI ethics grand challenge team; the Oden Institute for Computational Engineering and Sciences; and the Texas Advanced Computing Center (TACC).

See the article here:

UT Austin Selected as Home of National AI Institute Focused on Machine Learning - UT News | The University of Texas at Austin

More promising is the idea of participation as justice. Here, all members of the design process work together in tightly coupled relationships with frequent communication. Participation as justice is a long-term commitment that focuses on designing products guided by people from diverse backgrounds and communities, including the disability community, which has long played a leading role here. This concept has social and political importance, but capitalist market structures make it almost impossible to implement well.

Machine learning extends the tech industrys broader priorities, which center on scale and extraction. That means participatory machine learning is, for now, an oxymoron. By default, most machine-learning systems have the ability to surveil, oppress, and coerce (including in the workplace). These systems also have ways to manufacture consentfor example, by requiring users to opt in to surveillance systems in order to use certain technologies, or by implementing default settings that discourage them from exercising their right to privacy.

Given that, its no surprise that machine learning fails to account for existing power dynamics and takes an extractive approach to collaboration. If were not careful, participatory machine learning could follow the path of AI ethics and become just another fad thats used to legitimize injustice.

How can we avoid these dangers? There is no simple answer. But here are four suggestions:

Recognize participation as work.Many people already use machine-learning systems as they go about their day. Much of this labor maintains and improves these systems and is therefore valuable to the systems owners. To acknowledge that, all users should be asked for consent and provided with ways to opt out of any system. If they chose to participate, they should be offered compensation. Doing this could mean clarifying when and how data generated by a users behavior will be used for training purposes (for example, via a banner in Google Maps or an opt-in notification). It would also mean providing appropriate support for content moderators, fairly compensating ghost workers, and developing monetary or nonmonetary reward systems to compensate users for their data and labor.

Make participation context specific. Rather than trying to use a one-size-fits-all approach, technologists must be aware of the specific contexts in which they operate. For example, when designing a system to predict youth and gang violence, technologists should continuously reevaluate the ways in which they build on lived experience and domain expertise, and collaborate with the people they design for. This is particularly important as the context of a project changes over time. Documenting even small shifts in process and context can form a knowledge base for long-term, effective participation. For example, should only doctors be consulted in the design of a machine-learning system for clinical care, or should nurses and patients be included too? Making it clear why and how certain communities were involved makes such decisions and relationships transparent, accountable, and actionable.

Plan for long-term participation from the start. People are more likely to stay engaged in processes over time if theyre able to share and gain knowledge, as opposed to having it extracted from them. This can be difficult to achieve in machine learning, particularly for proprietary design cases. Here, its worth acknowledging the tensions that complicate long-term participation in machine learning, and recognizing that cooperation and justice do not scale in frictionless ways. These values require constant maintenance and must be articulated over and over again in new contexts.

Learn from past mistakes. More harm can be done by replicating the ways of thinking that originally produced harmful technology. We as researchers need to enhance our capacity for lateral thinking across applications and professions. To facilitate that, the machine-learning and design community could develop a searchable database to highlight failures of design participation (such as Sidewalk Labs waterfront project in Toronto). These failures could be cross-referenced with socio-structural concepts (such as issues pertaining to racial inequality). This database should cover design projects in all sectors and domains, not just those in machine learning, and explicitly acknowledge absences and outliers. These edge cases are often the ones we can learn the most from.

Its exciting to see the machine-learning community embrace questions of justice and equity. But the answers shouldnt bank on participation alone. The desire for a silver bullet has plagued the tech community for too long. Its time to embrace the complexity that comes with challenging the extractive capitalist logic of machine learning.

Mona Sloane is a sociologist based at New York University. She works on design inequality in the context of AI design and policy.

Here is the original post:

Participation-washing could be the next dangerous fad in machine learning - MIT Technology Review

Abeba Birhane: I study embodied cognitive science, which is at the heart of how people interact and go about their daily lives and what it means to be a person.

You recently made a big discovery that an academic library containing millions of images used to train artificial intelligence systems had privacy and ethics issues, and that it included racist, misogynistic and other offensive content.

Yes, I worked on this with Vinay Prabhu a chief scientist at UnifyID, a privacy start-up in Silicon Valley on the 80-million images dataset curated by Massachusetts Institute of Technology. We spent about months looking through this dataset, and we found thousands of images labelled with insults and derogatory terms.

Using this kind of content to build and train artificial intelligence systems, including face recognition systems, would embed harmful stereotypes and prejudices and could have grave consequences for individuals in the real world.

What happened when you published the findings?

The media picked up on it, so it got a lot of publicity. MIT withdrew the database and urged people to delete their copies of the data. That was humbling and a nice result.

How does this finding fit in to your PhD research?

I study embodied cognitive science, which is at the heart of how people interact and go about their daily lives and what it means to be a person. The background assumption is that people are ambiguous, they come to be who they are through interactions with other people.

It is a different perspective to traditional cognitive science, which is all about the brain and rationality. My research looks at how artificial intelligence and machine learning has limits in how it can understand and predict the complex messiness of human behaviour and social outcomes.

Can you give me an example?

If you take the Shazam app, it works very well to recognise a piece of music that you play to it. It searches for the pattern of the music in a database, and this narrow search suits the machine approach. But predicting a social outcome from human characteristics is very different.

As humans we have infinite potentials, we can react to situations in different ways, and a machine that uses numerable parameters cannot predict whether someone is a good hire or at risk of committing a crime in the future. Humans and our interactions represent more than just a few parameters. My research looks at existing machine learning systems and the ethics of this dilemma.

How did you get into this work?

I started in physics back home in Ethiopia, but when I came to Ireland there was so much paperwork and so many exams to translate my Ethiopian qualification that I decided to start from scratch.

So I studied psychology and philosophy and I did a masters [masters course had lots of elements neuroscience, philosophy, anthropology, and computer science, where we built computational models of various cognitive faculties and it is where I really found my place.

How has Covid-19 affected your research?

At the start of the pandemic, I thought this might be a chance to write up a lot of my project, but I found it hard to work at home and to unhook my mind from what was going on around the world.

I also missed the social side, going for coffee and talking with my colleagues about work and everything else. So I am glad to be back in the lab now and seeing my lab mates even at a distance.

Original post:

Getting to the heart of machine learning and complex humans - The Irish Times

Machine learning is transforming the way an Air Force office analyzes and certifies new flight configurations.

The Air Force SEEK EAGLE Office sets standards for safe flight configurations by testing and looking at historical data to see how different storeslike a weapon system attached to an F-16affect flight. A project AFSEO developed along with industry partners can now automate up to 80% of requests for analysis, according to the offices Chief Data Officer Donna Cotton.

The application is kind of like an eager junior engineer consulting a senior engineer, Cotton said. It makes the straightforward calls without any input, but in the hard cases it walks into the senior engineers office and says: Hey, I did a bunch of research and this is what I found out. Can you give me your opinion?

Cotton spoke at a Tuesday webinar hosted by Tamr, one of the industry partners involved in the project. Tamr announced July 30 AFSEO awarded the company a $60 million contract for its machine learning application. Two other companies, Dell and Cloudera, helped AFSEO take decades of historical data from simulations, performance studies and the like that were siloed across various specialities and organize them into a searchable data lake.

On top of this new data architecture, the machine learning application provided by Tamr searches through all the historical data to find past records that can help answer new safety recommendation requests automatically.

This tool is critical because the vast majority of AFSEOs flight certification recommendations are made by analogy, meaning using previous data rather than new flight tests. But in the past, data was disorganized and lacked unification. This made tracking down these helpful records a challenge for engineers.

Now, a cleaner AFSEO data lake cuts the amount of time engineers waste on looking for the information they need. Machine learning further speeds up the process by generating safety reports automatically while still keeping the professional engineers in the loop. Even when engineers need to produce original research, the machine learning application can smooth the process by collecting related records to serve as a jumping off point.

The new process helps AFSEO avoid doing costly flight tests while also increasing confidence that the team is making the safety certification correctly with all the information available to them, Cotton said.

We are able to be more productive, Cotton said. It's saving us a lot of money because for us, it's not about profit, but it's about hours. It's about how much effort are we going to have to use to solve or to answer a new request.

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Air Force Taps Machine Learning to Speed Up Flight Certifications - Nextgov

Machine learning has proven to be useful for insurance agents and brokers in various ways. These include capturing knowledge, skills, and expertise from a generation of insurance staff before they retire in the next 5 to 10 years and use it to train new employees.

FREMONT, CA: Technology has become the dominant force across all businesses in the last few years. Disruptive technologies like Artificial Intelligence (AI), machine learning, and natural language processing are improving rapidly and quickly, evolving from theoretical to practical applications. These technologies have also made an impact on insurance agents and brokers. Many people continue to view technology as their foe. They either believe that machines will eventually replace them, or that a machine can never do their job better than them. While this may not be true, some aspects of it are relatable. For instance, a machine will never be able to provide real-time advice as a live agent does. However, low cost and easy to use platforms are currently available that allow agents and brokers to take advantage of this technology to enhance their delivery of advice and expertise to prospects and clients.

Machine learning has proven to be useful for insurance agents and brokers in various ways. These include capturing knowledge, skills, and expertise from a generation of insurance staff before they retire in the next 5 to 10 years and use it to train new employees.

Employee Augmentation

It helps provide personalized answers for a wide range of insurance questions. Digital customers want to get answers for their questions anytime and not just when an agent's office is open.

Personalized Digital Answers

It helps create and deliver a digital annual account review for personal lines or small commercial insurance accountants. A robust analysis leads to client satisfaction, creates cross-selling opportunities, and reduces errors and omission problems for the agency.

Digital Account Review

Many believe that artificial intelligence and machine learning will be the end of insurance agents as a trusted source for adequate protection against financial losses. However, these technologies are a threat only for insurance agents that are simply order takers. Insurance agents and brokers that embrace the technologies will always find opportunities to grow.

These emerging technologies mustn't be seen as a bane but as a boon. Insurance agents and brokers need to work in tandem with the upgrades in technology and leverage it to the best use. It holds increased potential to enhance customer satisfaction and offer a higher quality of service.

See Also:Top Machine Learning Companies

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The Role of Artificial Intelligence and Machine Learning in the... - Insurance CIO Outlook

The decentralized finance (DeFi) space is growing rapidly. Oracle protocols like Chainlink, BAND and Gravity have experienced a significant increase in adoption in a cryptocurrency market thats still highly speculative and plagued by market manipulative and wash trading.

Fetch.ai, an open-access machine learning network established by former DeepMind investors and software engineers, has teamed up with Waves, an established, open-source blockchain protocol that provides developer tools for Web 3.0 applications.

As mentioned in an update shared with Crowdfund Insider:

[Fetch.ai and Waves will] conduct joint R&D for the purpose of bringing increased multi-chain capabilities to Fetch.ais system of autonomous economic agents (AEA). [They will also] push further into bringing DeFi cross-chain by connecting with Waves blockchain agnostic and interoperable decentralized cross-chain and oracle network, Gravity.

As explained in the announcement, the integration with Gravity will enable Fetch.ais Autonomous Economic Agents to gain access to data sources or feeds for several different market pairs, commodities, indices, and futures.

Fetch.ai and Waves aim to achieve closer integration with Gravity in order to provide seamless interoperability to Fetch.ai, making its blockchain-based AI and machine learning (ML) solutions accessible across various distributed ledger technology (DLT) networks.

As stated in the update, the integration will help with opening up new ways for all Gravity-connected communities to use Fetch.ais ML functionality within the comfort of their respective ecosystems.

As noted in another update shared with CI, a PwC report predicts that AI and related ML technologies may contribute more than $15 trillion to the world economy from 2017 through 2030. Gartner reveals that during 2019, 37% of organizations had adopted some type of AI into their business operations.

In other DeFi news, Chainlink competitor Band Protocol is securing oracle integration with Nervos, which is a leading Chinese blockchain project.

As confirmed in a release:

Nervos is a Chinese public blockchain thats tooling up for a big DeFi push. The project is building DeFi platforms with China Merchants Bank International and Huobi, and also became one of the first public blockchains to integrate with Chinas BSN. Amid the DeFi surge, Nervos is integrating Bands oracles to give developers access to real-world data like crypto price feeds.

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AI and Machine Learning Network Fetch.ai Partners Open-Source Blockchain Protocol Waves to Conduct R&D on DLT - Crowdfund Insider