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Addressing Machine Learning Trustworthiness in the U.S.

“Taxonomy of trust” is a categorisation method created by researchers to increase the reliability of probabilistic machine learning. The trust-breaking points in data analysis are defined and strategies to repair them are identified.

Probabilistic machine learning strategies employ complex ideas from probability theory to deal with ambiguity in judgement. The techniques are becoming a powerful resource for analysing data today. From predicting election outcomes to the effect of microloans on alleviating poverty, it has been used to guide various crucial choices across fields and applications.

However, mathematical precision and efficacy are only part of the picture. With machine learning, researchers make arbitrary decisions during average data analysis, which can add human mistakes. The MIT team tackled this issue head-on to increase users’ faith in the reliability of choices made using these methods.

Researchers like Tamara Broderick, an associate professor in EECS and a member of MIT’s Laboratory for Information and Decision Systems (LIDS), hope to draw attention to both well-studied and under-researched issues in the field of computer science.

” I find this categorisation useful, it reveals how people spend their awareness. I believe it’s hard to answer [the question], ‘is it fair to mathematise a significant practical issue in a certain way,” Broderick elaborated. It’s moving into a stricter realm, no longer just a mathematical problem.

The authors of a study released in February in Science Advances begin by identifying potential points of distrust during the data analysis process.

  • They make decisions about what data to gather,
  • To what extent do the models (or quantitative representations thereof) they are using reflect the nature of the real-world problem (or query) they are attempting to solve,
  • Analysts pick algorithms to fit the model and use code to execute those algorithms.

There are unique difficulties in establishing confidence at each of these stages. There are quantifiable methods for verifying the correctness of certain parts. For instance, we can use quantitative criteria to find the answer to questions like “Does my code have bugs?”. Conversely, some issues are less black-and-white and require analysts to employ various methods to collect information and determine if a model represents the actual world.

Co-author Meager investigated the potential beneficial impact of microfinance on local communities. The initiative served as a case study to examine possible points of distrust and identify strategies for mitigating them. Microfinancing’s potential effect may seem easy to gauge at first glance.

Meager used statistics from microfinance initiatives in various nations, including the Philippines, Mongolia, Bosnia, and Mexico, to conduct her analysis. Researchers must determine if individual case studies can be generalised to a larger population when merging datasets with glaring differences from multiple countries and cultural contexts. Putting the available facts in perspective is also crucial.

Checking the code that executes an algorithm can feel “prosaic” while trying to distil a real-world issue into a model can feel as “big picture” and “amorphous”. However, this is yet another place where confidence can be improved but is at risk of being overlooked.

Verifying that code can be reproduced is an excellent method to find flaws. For example, Gelman and his co-authors analysed state and national surveys to predict the outcome of the 2020 U.S. presidential election in real-time. The crew posted the code details online and the result in a national magazine daily. Throughout the season, online observers flagged the model’s technical and philosophical flaws, leading to a more robust evaluation.

However, depending on the subject, code is only sometimes expected to be made public alongside a written work. The evaluation as early as possible is needed because writing new code from the start gets more challenging as model intricacy rises. It becomes problematic, to replicate a blueprint. The authors concede that there is no silver bullet for developing a flawless model but that there are numerous opportunities for analysts and scientists to bolster confidence.

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Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

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CTC Global Singapore, a premier end-to-end IT solutions provider, is a fully owned subsidiary of ITOCHU Techno-Solutions Corporation (CTC) and ITOCHU Corporation.

Since 1972, CTC has established itself as one of the country’s top IT solutions providers. With 50 years of experience, headed by an experienced management team and staffed by over 200 qualified IT professionals, we support organizations with integrated IT solutions expertise in Autonomous IT, Cyber Security, Digital Transformation, Enterprise Cloud Infrastructure, Workplace Modernization and Professional Services.

Well-known for our strengths in system integration and consultation, CTC Global proves to be the preferred IT outsourcing destination for organizations all over Singapore today.

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Planview has one mission: to build the future of connected work. Our solutions enable organizations to connect the business from ideas to impact, empowering companies to accelerate the achievement of what matters most. Planview’s full spectrum of Portfolio Management and Work Management solutions creates an organizational focus on the strategic outcomes that matter and empowers teams to deliver their best work, no matter how they work. The comprehensive Planview platform and enterprise success model enables customers to deliver innovative, competitive products, services, and customer experiences. Headquartered in Austin, Texas, with locations around the world, Planview has more than 1,300 employees supporting 4,500 customers and 2.6 million users worldwide. For more information, visit www.planview.com.

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SIRIM is a premier industrial research and technology organisation in Malaysia, wholly-owned by the Minister​ of Finance Incorporated. With over forty years of experience and expertise, SIRIM is mandated as the machinery for research and technology development, and the national champion of quality. SIRIM has always played a major role in the development of the country’s private sector. By tapping into our expertise and knowledge base, we focus on developing new technologies and improvements in the manufacturing, technology and services sectors. We nurture Small Medium Enterprises (SME) growth with solutions for technology penetration and upgrading, making it an ideal technology partner for SMEs.

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HashiCorp provides infrastructure automation software for multi-cloud environments, enabling enterprises to unlock a common cloud operating model to provision, secure, connect, and run any application on any infrastructure. HashiCorp tools allow organizations to deliver applications faster by helping enterprises transition from manual processes and ITIL practices to self-service automation and DevOps practices. 

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IBM is a leading global hybrid cloud and AI, and business services provider. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.

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