Recent years have seen growing adoption of AI-based decision-support systems (ADS) in homeless services, yet we know little about stakeholder desires and concerns surrounding their use. In this work, we aim to understand impacted stakeholders' perspectives on a deployed ADS that prioritizes scarce housing resources. We employed AI lifecycle comicboarding, an adapted version of the comicboarding method, to elicit stakeholder feedback and design ideas across various components of an AI system's design. We elicited feedback from county workers who operate the ADS daily, service providers whose work is directly impacted by the ADS, and unhoused individuals in the region. Our participants shared concerns and design suggestions around the AI system's overall objective, specific model design choices, dataset selection, and use in deployment. Our findings demonstrate that stakeholders, even without AI knowledge, can provide specific and critical feedback on an AI system's design and deployment, if empowered to do so.

Tractian, a machine intelligence company offering one of the most advanced industrial monitoring systems on the market, announced $15 million in Series A funding led by Next47, a global venture capital firm specializing in building category-defining B2B technology businesses. YCombinator and other previous investors also participated in the round. The new capital will allow the company to consolidate its position in the global market by extending operations from Brazil to Mexico and the U.S. and continuing rapid development of industry-leading products. "We know the industries that empower their frontline workers with best-in-class productivity tools have superpowers compared to others, and Tractian appears as the right arm of maintenance managers to manage their routines around the world" Tractian has developed streamlined hardware-software solutions designed to give maintenance technicians and decision-makers comprehensive oversight of their operations. With ease of installation and quick value generation at the heart of its customer approach, Tractian is democratizing access to sophisticated monitoring and analytics.

In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting disease COVID-19 were first identified in Wuhan China. The disease slipped through containment measures, with the first known case in the United States being identified on January 20th, 2020. In this paper, we utilize survey data from the Inter-university Consortium for Political and Social Research and apply several statistical and machine learning models and techniques such as Decision Trees, Multinomial Logistic Regression, Naive Bayes, k-Nearest Neighbors, Support Vector Machines, Neural Networks, Random Forests, Gradient Tree Boosting, XGBoost, CatBoost, LightGBM, Synthetic Minority Oversampling, and Chi-Squared Test to analyze the impacts the COVID-19 pandemic has had on the mental health of frontline workers in the United States. Through the interpretation of the many models applied to the mental health survey data, we have concluded that the most important factor in predicting the mental health decline of a frontline worker is the healthcare role the individual is in (Nurse, Emergency Room Staff, Surgeon, etc.), followed by the amount of sleep the individual has had in the last week, the amount of COVID-19 related news an individual has consumed on average in a day, the age of the worker, and the usage of alcohol and cannabis.

Many companies struggle to reap the benefits of investments in digital transformation, while others see enormous gains. What do successful companies do differently? This article describes the five stages of digital transformation, from the traditional stage, where digital and technology are the province of the IT department, through to the platform stage, where a comprehensive software foundation enables the rapid deployment of AI-based applications. The ideal is the native stage, whose hallmarks are an operating architecture designed to deploy AI at scale across a huge, distributed spectrum of applications; a core of experts; broadly accessible, easy-to-use tools; and investment in training and capability-building among large groups of businesspeople. Over the past decade, Novartis has invested heavily in digital transformation.

As AI in manufacturing changes how machine health is monitored and managed, companies will need machine ops specialists to bridge the gap between operations and maintenance. AI in manufacturing can enable the digital transformation of the industry into a more effective, skillful, and productive version of itself. It can help enhance record-keeping, inventory management, and supply chain flow. Through machine data analysis, it can also significantly improve machine health. AI can diagnose existing problems and provide predictive insights to save manufacturers time and money on maintenance and repairs.

The pandemic ushered us all into this experience together, and now that we have "graduated" into a post-pandemic world, we can reflect on the lessons it has taught us. The lessons include living and working together to create a world and organisation unified by a purpose. It also helped shake the mindset of the global economy as we strived to make the impossible possible. Instead of employees following a fixed schedule, it has transitioned to employees being on-demand as per their choice of time and place. As a result, employees are now free from the office walls - it is limitless, and they can meet the needs of their companies and consumers.

Applying for a frontline job can be a game of hurry-up-and-wait, and communication is not always the best when a company is trying to fill dozens of positions at the same time. Enter Emi, the latest company targeting technology to this portion of the workforce with a conversational artificial intelligence recruiting tool. The technology automates communication between global enterprises and candidates using a conversational interface. CEO Mateo Cavasotto says this reduces the time it takes to hire people, while also increasing candidate satisfaction, thus improving recruitment productivity. The idea for the company came a couple of years ago when Cavasotto and Andres Arslanian, CTO, worked as volunteers for a Microcredits NGO in Argentina. They were working to understand how problems among the poverty-stricken population could be solved with technology.

Unpredictable spikes and drops in demand combined with chronic supply chain and labor shortages are accelerating the pace of digital transformation in manufacturing, starting with worker safety. Forty-eight percent of manufacturers say their progress on digital transformation initiatives has accelerated so much that it's years ahead of what was originally anticipated, according to a KPMG study. Keeping workers safe and connected is the primary goal of most digital transformation and hiring plans, with on-site distancing & workplace safety listed as the two highest priorities. The company's SENTRI360 platform proves effective in preventing workplace injuries and operational downtimes at several steel-heavy manufacturing companies, including Zekelman Industries and SeAH Besteel. From redesigning shop floors, to meeting social distancing guidelines, and doubling their investment in training and development, worker safety now dominates manufacturing -- even more so due to the pandemic.

Unpredictable spikes and drops in demand combined with chronic supply chain and labor shortages are accelerating the pace of digital transformation in manufacturing, starting with worker safety. Forty-eight percent of manufacturers say their progress on digital transformation initiatives has accelerated so much that it's years ahead of what was originally anticipated, according to a KPMG study. Keeping workers safe and connected is the primary goal of most digital transformation and hiring plans, with on-site distancing & workplace safety listed as the two highest priorities. The company's SENTRI360 platform proves effective in preventing workplace injuries and operational downtimes at several steel-heavy manufacturing companies, including Zekelman Industries and SeAH Besteel. From redesigning shop floors, to meeting social distancing guidelines, and doubling their investment in training and development, worker safety now dominates manufacturing -- even more so due to the pandemic.

Sometimes friends ask me what do I do, and then they ask what is customer experience research is for? The simple answer I give is that employees dealing with customers should get feedback on how the customer views the experience. Only this way they can learn and improve. This idea is also referred to as the INNER LOOP. It is contrasted with the OUTER LOOP, which tries to initiate learnings from feedback and conclude strategic initiatives for change. The Inner Loop is set up to make customer-facing employees learn how customers perceive them, give them praise in case of great feedback, but also give an opportunity to follow up with detractors and complaints quickly.