Years of software engineering and product development have taught us that the best way to build products that delight customers is to talk to customers. Talking to actual customers provides important insights into their challenges and their loves. This leads to innovative and creative ways of solving problems (without creating new ones) and guards against ruining the workflows customers already enjoy. And yet, the emergence of artificial intelligence (AI) has many leaders forgetting these lessons in a rush to create new AI-driven development tools, often without consulting actual developers. Our research is meant to help close that gap and give companies, product teams, and fellow practitioners insights into the opportunities and concerns that developers have with using AI in their work. Armed with this information, product teams and leaders can make better product decisions and communicate more effectively about the changes happening around them.

Amidst decline in public trust in technology, computing ethics have taken center stage, and critics have raised questions about corporate ethics washing. Yet few studies examine the actual implementation of AI ethics values in technology companies. Based on a qualitative analysis of technology workers tasked with integrating AI ethics into product development, we find that workers experience an environment where policies, practices, and outcomes are decoupled. We analyze AI ethics workers as ethics entrepreneurs who work to institutionalize new ethics-related practices within organizations. We show that ethics entrepreneurs face three major barriers to their work. First, they struggle to have ethics prioritized in an environment centered around software product launches. Second, ethics are difficult to quantify in a context where company goals are incentivized by metrics. Third, the frequent reorganization of teams makes it difficult to access knowledge and maintain relationships central to their work. Consequently, individuals take on great personal risk when raising ethics issues, especially when they come from marginalized backgrounds. These findings shed light on complex dynamics of institutional change at technology companies.

At Too Good To Go, we have an ambitious goal: to inspire and empower everyone to fight food waste together. And that has a huge impact on the health of our planet, with 10% of greenhouse gas emissions coming from food waste. We're more than an app: we are a certified B Corporation with a mission to empower everyone to take action against food waste, so alongside our marketplace app, we create educational tools, explore new business solutions - such as our Retail Technologies offering, and influence legislation to help reduce food waste. We are growing fast, with a community of 73 million users in 17 countries. Together, we have saved more than 200 million meals from going to waste since we started - but there's still a lot more we want to achieve We are looking for Machine Learning Engineer to be a part of our Product Teams that define, build and deliver our product features.

This paper reports on our initial evaluation of The Equitable AI Research Roundtable -- a coalition of experts in law, education, community engagement, social justice, and technology. EARR was created in collaboration among a large tech firm, nonprofits, NGO research institutions, and universities to provide critical research based perspectives and feedback on technology's emergent ethical and social harms. Through semi-structured workshops and discussions within the large tech firm, EARR has provided critical perspectives and feedback on how to conceptualize equity and vulnerability as they relate to AI technology. We outline three principles in practice of how EARR has operated thus far that are especially relevant to the concerns of the FAccT community: how EARR expands the scope of expertise in AI development, how it fosters opportunities for epistemic curiosity and responsibility, and that it creates a space for mutual learning. This paper serves as both an analysis and translation of lessons learned through this engagement approach, and the possibilities for future research.

V.EV, Vitol's fleet electrification business, offers a turnkey fleet electrification solution to fleets of all vehicle types. By offering an end to end service to identify the right solution to enable fleets to decarbonise, the provision and installation of charging infrastructure and the subsequent operation of your fleet's chargepoints, battery storage and onsite generation through our software solution we can accelerate the rate the UK's fleets decarbonise. Our parent company is the world's largest independent energy and commodities trading company. From 40 offices worldwide, Vitol seek to add value across the energy supply chain, including deploying its scale and market understanding to help facilitate the energy transition. To date, Vitol committed over $2.2 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world.

Wolt is a technology company that makes it incredibly easy to discover and get the best restaurants, grocery stores and other local shops delivered to your home or office. Wolt is not just a delivery app – we're a technology company building a global logistics platform to seamlessly connect our millions of customers with thousands of merchant and courier partners, in real-time across 23 countries and 250 cities. Our apps (iOS and Android) have the industry's highest ratings, largely thanks to our customer-first-mindset, which shows in how we build products and run operations. At Wolt, we're about getting things done. You'll probably enjoy it here if you like taking ownership, developing yourself and being around friendly, humble and ambitious people.

Also of note is the evolution of MLops platforms, which are making it possible to set up complete pipelines for gathering feedback data, versioning datasets and models, and fine-tuning models for specific applications.

The race to create Intelligent products is here and with that comes a need to understand the potential of what Machine and Deep Learning can do so that future products and services can be designed, developed and marketed. This blog discusses the need for Product Managers to embrace Artificial Intelligence (AI). This is something that keeps every Chief Executive Office (CEO) up at night – future revenue based on future products. The scenario is this: your top competitor launches a new version of their product that is predictive and intelligent. Your team has no plan in place.

Checkr's mission is to build a fairer future by designing technology to create opportunities for all. We believe all candidates, regardless of who they are, should have a fair chance to work. Established in 2014 and valued at $5B, Checkr is using technology to bring hiring to the next level. Our People Trust Platform uses machine learning to help thousands of companies modernize their background check process and make hiring safer, more efficient, and more inclusive. Some of our customers include Uber, Instacart, Doordash, Netflix, Compass Group, and Adecco.

Toronto artificial intelligence (AI) startup Ada is bolstering its tech stack with a new machine learning centre in Israel and the appointment of a chief product officer (CPO). "The motivation to open the machine learning centre in Israel stems from the pool of talent there in conversational AI and in machine learning." This week, Ada announced the opening of its office in Israel, where it will be hiring machine learning, engineering, and product teams to continue to develop the conversational AI systems that power its automated brand interaction platform. Israel's growing AI market is what attracted Ada to make inroads into the country, according to the startup. Research firm Tracxn estimates that there are currently 1,100 startups in Israel that use AI as a core component of their offering.