Machine learning

National Science Foundation, in collaboration with Amazon, awards 11 Fairness in AI grant projects

Program supports computational research with goal of creating trustworthy AI systems that can address some of society's grand challenges.

By Staff writer
February 10, 2021
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  1. In 2019, the National Science Foundation (NSF) and Amazon announced a collaboration to accelerate research on fairness in AI, with each organization committing up to $10 million each in grants over the ensuing three years.

    Last year, NSF announced the first 10 projects to receive grants through the initiative. Thirty-five researchers obtained funds for the projects that addressed four broad research areas:

    1. Ensuring fairness in algorithms and the systems that incorporate them — which begins with the definition and quantification of fairness;
    2. Accountability and transparency in AI algorithms;
    3. Using AI to promote equity in society; and
    4. Ensuring that the benefits of AI are available to everyone.

    This year, NSF has announced the next cohort of 37 researchers focused on 11 projects that cover a range of topics, including:

    1. Theoretical and algoithmic foundations;
    2. Principles for human interaction with AI systems;
    3. Technologies such as natural language understanding and computer vision; and
    4. Applications including hiring decision, education, criminal justice, and human services.

    “We are excited to see NSF select an incredibly talented group of researchers whose research efforts are informed by a multiplicity of perspectives,” said Prem Natarajan, Alexa AI vice president of Natural Understanding. “As AI technologies become more prevalent in our daily lives, AI fairness is an increasingly important area of scientific endeavor. And we are delighted to partner with NSF to accelerate progress in this area by supporting the work of the top research teams in the world.”

    Henry Kautz, NSF
    Henry Kautz, NSF
    Credit: NSF

    “NSF is partnering with Amazon to support this year’s cohort of fairness in AI projects,” said Henry Kautz, director of NSF’s Division of Information and Intelligent Systems. “Understanding how AI systems can be designed on principles of fairness, transparency and trustworthiness will advance the boundaries of AI applications. And it will help us build a more equitable society in which all citizens can be designers of these technologies as well as benefit from them.”

    More information about this Fairness in AI
    program is available on NSF's website, and via their program update. Below is the list of the 2021 awardees, and an overview of their projects.

  2. Fairness in machine learning with human in the loop

    "This project aims to understand the long-term impact of fair decisions made by automated machine learning algorithms via establishing an analytical, algorithmic, and experimental framework that captures the sequential learning and decision process, the actions and dynamics of the underlying user population, and its welfare."

    • Principal investigator: Yang Liu
    • Co-principal investigators: Mingyan Liu, Parinaz Naghizadeh Ardabili, Ming Yin
    • Organization: University of California Santa Cruz
    • Award amount: $625,000

    Project description

  3. End-to-end fairness for algorithm-in-the-loop decision-making in the public sector

    "The goal of this project is to develop methods and tools that assist public sector organizations with fair and equitable policy interventions. In areas such as housing and criminal justice, critical decisions that impact lives, families, and communities are made by a variety of actors, including city officials, police, and court judges..." 

    • Principal investigator: Daniel Neill
    • Co-principal investigators: Constantine Kontokosta, Ravi Shroff, Edward McFowland
    • Organization: New York University
    • Award amount: $625,000

    Project description

  4. Foundations of fair AI in medicine: ensuring the fair use of patient attributes

    "Currently deployed machine learning models in medicine may exhibit fair use violations that undermine health outcomes. This project mitigates fair use violations at key stages in the deployment of machine learning in medicine: verification, model development, and communication..." 

    • Principal investigator: Flavio Calmon
    • Co-principal investigators: Elena Glassman, Berk Ustun
    • Organization: Harvard University
    • Award amount: $625,000

    Project description

  5. Organizing crowd audits to detect bias in machine learning

    "This project will explore three major research questions. The first is investigating new techniques for recruiting and incentivizing participation from a diverse crowd. The second is developing new and effective forms of guidance for crowd workers for finding instances and generalizing instances of bias. The third is designing new ways of synthesizing findings from the crowd so that development teams can understand and productively act on..."

    • Principal investigator: Jason Hong
    • Co-principal investigators: Motahhare Eslami, 
      Ken Holstein, Adam Perer, Nihar Shah
    • Organization: Carnegie-Mellon University
    • Award amount: $625,000

    Project description

  6. Using machine learning to address structural bias in personnel selection

    "Today, personnel selection practitioners in the United States are primarily guided by two streams of knowledge: 1) the development on the legal front pertaining to employment opportunities, and 2) the accumulation of findings in social, behavioral, and economic sciences that guide the accepted professional practices in personnel selection... This research project focuses on bridging the gap to establish machine learning as the third pillar for the design of personnel selection systems in human resource management..."
     

    • Principal investigator: Nan Zhang
    • Co-principal investigators: Heng Xu, Mo Wang
    • Organization: American University
    • Award amount: $624,485
      Project description
  7. Towards adaptive and interactive post hoc explanations

    "This proposal has three key areas of focus. First, this proposal will develop a novel formal framework for generating adaptive explanations which can be customized to account for subgroups of interest and user profiles. Second, this proposal will facilitate the explanations as an interactive communication process by dynamically incorporating user inputs. Finally, this proposal will improve existing automatic evaluation metrics such as sufficiency and comprehensiveness, and develop novel ones, especially for the understudied global explanations..."

    • Principal investigator: Chenhao Tan
    • Co-principal investigators: Yuxin Chen, Himabindu Lakkaraju, Sameer Singh
    • Organization: University of Chicago
    • Award amount: $375,000

    Project description

  8. Using AI to increase fairness by improving access to justice

    "This project applies Artificial Intelligence (AI) to increase social fairness by improving public access to justice. Although many AI tools are already available to law firms and legal departments, these tools do not typically reach members of the public and legal service practitioners except through expensive commercial paywalls. The research team will develop two tools to make legal sources more understandable: Statutory Term Interpretation Support (STATIS) and Case Argument Summarization (CASUM)..."

    • Principal investigator: Kevin Ashley
    • Co-principal investigators: Diane Litman
    • Organization: University of Pittsburgh
    • Award amount: $375,000

    Project description

  9. Fair AI in public policy - achieving fair societal outcomes in ML applications to education, criminal justice, and health and human services

    "This project advances the potential for Machine Learning (ML) to serve the social good by improving understanding of how to apply ML methods to high-stakes, real-world settings in fair and responsible ways..."

    • Principal investigator: Hoda Heidari
    • Co-principal investigators: Olexandra Chouldechova, Rayid Ghani, Zachary Lipton, Christopher Rodolfa
    • Organization: Carnegie-Mellon University
    • Award amount: $375,000

    Project description

  10. Towards holistic bias mitigation in computer vision systems

    "With the increasing use of artificial intelligence (AI) systems in life-changing decisions, such as hiring or firing of individuals or the length of jail sentences, there has been an increasing concern about the fairness of these systems. There is a need to guarantee that AI systems are not biased against segments of the population. This project aims to mitigate AI bias in the domain of computer vision, a driving application for much of the recent advances in a popular form of AI known as deep learning..."

    • Principal investigator: Nuno Vasconcelos
    • Organization: University of California San Diego
    • Award amount: $375,000
    • Project description
  11. Measuring and mitigating biases in generic image representation

    "This project will provide a study of societal biases present in current methods and models for computational visual recognition that are widely used as a source of generic visual representations..."

    • Principal investigator: Vicente Ordonez
    • Co-principal investigators: Baishakhi Ray
    • Organization: University of Virginia
    • Award amount: $375,000

    Project description

  12. Quantifying and mitigating disparities in language technologies

    "In this work we ask a simple question: can we measure the extent to which the diversity of language that we use affects the quality of results that we can expect from language technology systems? This will allow for the development and deployment of fair accuracy measures for a variety of tasks regarding language technology, encouraging advances in the state of the art in these technologies to focus on all, not just a select few..."

    • Principal investigator: Graham Neubig
    • Co-principal investigators: Jeffrey Bigham, Yulia Tsvetkov, Geoff Kaufman, Antonios Anastasopoulos
    • Organization: Carnegie-Mellon University
    • Award amount: $375,000

    Project description

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CV&ML Applied Scientist
US, WA, Seattle
This early-stage initiative is tackling problems that span a variety of domains: computer vision, machine learning, Human-Computer-Interaction and real-time systems.As a Computer Vision Applied Scientist you will help solve a variety of technical challenges and mentor other team members while actively following our entrepreneurial culture that encourages us to wear many hats. You will play an active role in leading translation of business and functional requirements into concrete deliverables. Build quick prototypes and proofs of concept in partnership with other technology leaders within the team. Improve products and concepts as a direct result of your research while delivering significant benefits to business.You are well versed in the relevant literature and will have the ability to find, understand and adapt new state of the art methods from the core discipline as well as beyond to create breakthrough problem-solution pairs. You will tackle challenging, novel situations every day and you’ll have the opportunity to work with other technical teams at Amazon within and outside the organization. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that haven’t been dreamed up and much less solved at scale before - anywhere. Along the way, you’ll learn a ton, have fun and make a positive impact on millions of people.Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Alexa Shopping - Senior Data Scientist
US, CA, Sunnyvale
Our Alexa Product Advisor (part of Alexa Shopping) vision is to provide the best possible answers for a wide range of questions around product being asked by the customer. The first step in providing these answers is to form high quality classification and machine understanding of natural language questions into their core components (shape, product references, attributes, pronouns etc).Alexa Shopping is looking for an experienced Sr Data Scientist to be a part of a team solving complex natural language processing problems and customer demand insights (including segmentation analysis and personas building using big data, ML and potentially AI). This is a blue-sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build simulations and experimentation systems at scale, build optimization algorithms and leverage cutting-edge technologies across Amazon. This is an opportunity to think big about how to solve a challenging problem for the customers and understand their requirements for products.You will work closely with product and technical leaders throughout Alexa Shopping and will be responsible for influencing technical decisions in areas of development/modelling that you identify as critical future product offerings. You will identify both enablers and blockers of adoption for product understanding, and build programs to raise the bar in terms of understanding product questions and predict the shaping of customer utterances as we move from simple to complex utterances.The ideal candidate will have extensive experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities in sourcing processes. Excellent business and communication skills are a must to develop and define key business questions and to build data sets that answer those questions. You should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges. Further, you must have the ability to build and communicate compelling value propositions, and work across the organization to achieve consensus. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results.
Senior Applied Scientist
US, WA, Seattle
Amazon Performance Advertising sits at the intersection of e-commerce and advertising, developing new native advertising experiences that are a critical area of strategic focus for the company. Amazon Sponsored Brands is an always-on advertising product that amplifies brand content to shoppers researching on Amazon through prominent cost-per-click ads. As we move up the purchase funnel, and create more touch points for shoppers, Sponsored Brands plays a key role in the discoverability and reach of brand content. Amazon Sponsor Brands is looking for a scientist to lead innovation for our global advertising marketplace. At the heart of our advertising business are systems for optimizing the ad marketplace involving sourcing and targeting, experimentation infrastructure, AI methods for inference and control, as well as metrics-driven closed loop optimizations.Job Responsibilities:· Design, develop, and productionize end-to-end machine learning solutions.· Work closely with software engineers and data scientists on detailed requirements, technical designs and implementation of end-to-end solutions in production· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences· Help attract, lead, and mentor technical talent.Impact and Career Growth:· You will invent new shopper and advertiser experiences, and accelerate the pace of Machine Learning and Optimization.· Influence customer facing shopping experiences to helping suppliers grow their retail business and the auction dynamics that leverage native advertising, this role will be powering the engine of one the fastest growing businesses at Amazon.· Define a long-term science vision for our ad marketplace, driven fundamentally from the needs of our customers, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This is a role that combines science leadership, organizational ability, technical strength, product focus and business understanding.Why you love this opportunity:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.
Principle Applied Scientist
US, VA, Arlington
We are developing advanced technologies that enhance the experience of shoppers in physical stores. Designed and custom-built by Amazon, existing products such as the Amazon Dash Cart and Amazon Go integrate a variety of advanced technologies including computer vision, sensor fusion, and advanced machine learning.We are seeking talented people who want to join an ambitious research and development program that who will help us define the future of physical retail. As a Principle Applied Scientist, you will architect systems that involve addressing complex technical challenges while meeting stringent performance and robustness goals. You will mentor other engineers and ensure they are producing state-of-the-art solutions while also continuing to advance their knowledge and capabilities. You will play an active role in guiding the development of research infrastructure for real-time machine learning and you will play a key role in translating technology solutions into real-world systems in partnership with other product organizations.You will tackle challenging situations every day and you’ll have the opportunity to work with multiple technical teams at Amazon. You should be comfortable with a high degree of ambiguity and have the communication skills necessary to articulate strategic approaches that both address immediate product needs and which set your team up for future success. Along the way, we guarantee that you’ll learn a lot, have fun, and make a positive impact on many customersIn this role:• You will encounter challenging, open-ended technical problems to solve, with solutions that span the entire implementation stack from devices to real-time algorithms to cloud-based services.• You will be able to demonstrate your strong technical and communication skills as well as your leadership abilities to deliver brand new customer experiences on behalf of Amazon.• You must be curious in the face of ambiguity and able to develop prototypes and perform experiments to create robust, scalable, distributed and fault-tolerant features to enhance the experience of Amazon customers around the globe.NOTE re: LOCATION: The main location for this job is the Washington DC metro region.
Sr Mgr, Science Product
US, WA, Seattle
Within Alexa Shopping, we are forming a new, insurgent team to better serve Alexa customers who are less engaged with Amazon stores. This is a large cohort of customers who want to use Alexa as their Shopping assistant and we want to meet the particular needs of these customers. The first job is to understand these customers better, how they shop in and out of Amazon stores, how they use Alexa and Alexa Shopping features, and what gaps remain between their needs and the features we have today.A day in the lifeYou will use data science to better understand how we can fulfill Alexa Shopping’s aspirations to be the anywhere shopping AI for with a focus on customers who are less engaged with Amazon. In the first months on the job, you will hire a new team and undertake a deep dive on this customer cohort using data on Amazon shopping behaviors, Alexa feature usage and primary research on their needs. This deep dive will lead to specific marketing program, feature and product ideas. You will influence the most senior leaders in the Alexa Shopping organization to steer marketing and feature roadmaps in order to better serve these customers. In the first year, you will write several PRFAQs for new feature and product ideas and you will advocate for them at the highest levels of the organization.About the hiring groupAt Alexa Shopping, we strive to enable shopping in everyday life through technology innovations in both voice and screen applications, from organizing shopping to covering in the moment shopping needs. We allow customers to create, add to, and collaborate on shopping lists that can be used in any store and to instantly order whatever they need, by simply interacting with their Smart Devices such as Echo or Fire TV. Our products range from package tracking to shopping lists and instant ordering, and with these capabilities we seek to make advertising more actionable and useful to customers. The business is both focused on generating value for shoppers as well as advertisers.Job responsibilities· Use data science to understand the shopping behaviors and needs of Alexa customers who are less engaged in Amazon stores· Hire and develop a nimble team of insurgents· Identify marketing and product gaps between our current feature portfolio and the needs of this customer cohort· Develop and experiment with product, feature and program ideas (e.g. write PRFAQs) and advocate for them at the highest levels of leadership in the organizationAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Applied Scientist
US, WA, Bellevue
Join us in a historic endeavor to make Computer Vision accessible to the world with breakthrough research!The AWS Computer Vision science team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists have developed the algorithms and models that power AWS computer vision services such as Amazon Rekognition and Amazon Textract. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world.Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods, active learning and semi-automated data annotation, large scale image and video detection and recognition, face detection and recognition, OCR and scene text recognition, document understanding, and 3D scene and layout understanding.We are located in Seattle, Pasadena, Palo Alto, Atlanta (USA) and in Haifa and Tel Aviv (Israel).Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Applied Scientist - Personalization
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office. You will be responsible for developing and disseminating customer-facing personalized recommendation algorithms. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization.You will design deep learning algorithms that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside more senior team members to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization.Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide.Key responsibilities· Develop deep learning algorithms for high-scale recommendations problem· Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement.· Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency.· Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
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