AI Deployment Strategist Intern

Scale AI acquires ICG Solutions to provide the U.S. Department of War and the broader Intelligence Community the most advanced, reliable AI infrastructure available.

Meta-linked Scale AI faces scrutiny over data scraping by gig workers. Contractors say tasks went beyond training models into handling personal and sensitive data. AI training under scrutiny as workers flag data scraping and ethical concerns * AI gig workers raise concerns over data use and working conditions * Tasks reportedly included social media scraping and sensitive content * Industry faces growing questions over ethics and transparency The rapid rise of artificial intelligence has created a vast, largely unseen workforce tasked with training the systems that power it. But new accounts from workers linked to Scale AI suggest the reality of that work may be more complicated than advertised. Scale AI, partly owned by Meta, runs a platform called Outlier, where contractors are recruited to help refine AI models. The work is often pitched as flexible, skilled employment for people with backgrounds in fields such as medicine, economics and science. However, several workers say the tasks extended well beyond technical training. Instead, they described assignments involving scraping social media platforms like Facebook and Instagram, tagging individuals and analysing personal content. One contractor reportedly said users would be surprised to know how their data was being handled. "I don't think people understood quite that there'd be somebody... looking at your profile, using it to generate AI data," they said, as quoted in a news report. From expert tasks to uncomfortable assignments. Workers who spoke about their experience said the nature of assignments could vary widely, and at times become difficult to handle. Some described being asked to transcribe explicit audio content or label distressing images. Others said they encountered material they had not expected, including violent scenarios or sensitive imagery. One doctoral student said they had been assured certain content would not appear, but later encountered otherwise. "We had already been told... no nudity... no gore," they reportedly said. "But then I would get an audio transcript thing for porn," as quoted in a news report. Beyond content concerns, there were also questions about how data was sourced. Several workers said they were asked to analyse publicly available social media profiles, including identifying people, locations and relationships. Some assignments, they claimed, appeared to involve data from younger users as well. A source familiar with the company's operations said tasks do not involve private accounts and that contributors are not required to engage with material they find uncomfortable. A growing industry with blurred lines. The scale of this kind of work is expanding quickly. Glenn Danas, a lawyer representing AI gig workers, estimates that hundreds of thousands of people globally are now involved in similar roles across platforms. Many workers said they took on the work as a way to supplement income, particularly in a labour market where AI itself is beginning to reshape job opportunities. At the same time, concerns about pay and conditions have emerged. Some workers described inconsistent earnings and a project-based system where tasks could disappear without notice. Others alleged recruitment practices that promised higher pay than what was ultimately offered, though the company has disputed this. There were also reports of monitoring software being used during tasks. Workers said tools could track activity and capture screenshots, while a source said such systems are intended to ensure accurate payment rather than continuous surveillance. Scale AI has said its platform offers flexible, project-based work and that contributors can choose when and how they participate. Questions over data, ownership and the future. The situation highlights a broader issue facing the AI industry. As models grow more advanced, the demand for large volumes of labelled data continues to increase. That data often comes from real-world sources, raising questions about consent, ownership and usage. Scale AI has worked with major technology firms including Google and OpenAI, as well as government clients. Some workers said they believed their tasks were contributing to training systems used across the industry. At the same time, many expressed uncertainty about what exactly they were helping to build. One worker reportedly questioned why certain tasks were necessary, noting that some appeared repetitive or unclear in purpose. Despite these concerns, most said they continue to take on assignments. For many, the work remains one of the few accessible options in a changing job market shaped increasingly by automation. "I have to be positive about AI because the alternative is not great," one worker reportedly said. The debate around AI is often framed in terms of future potential. But for those already working behind the scenes, the questions appear more immediate - about how data is used, how workers are treated, and where the boundaries should be drawn. All-Inclusive Resort in Riviera NayaritResort on Punta de Mita's stunning beaches. All-inclusive: food, cocktails, and activities at Grand Palladium Vallarta. Plus, a laid-back paradise for surfers!Palladium Hotel Group | Sponsored

Qatar eyes a bigger role in AI with full-stack investments. Doha, Qatar - Qatar is building its artificial intelligence strategy across multiple layers of the technology stack, combining sovereign investment, talent development, startup support, and domestic computing infrastructure as it works to position itself as a regional hub for AI. Recent activity around Web Summit Qatar 2026 points to a coordinated approach that goes beyond backing individual companies and instead focuses on building an ecosystem that can support AI development, deployment, and commercial adoption over time. Investing from hardware to inference. One of the clearest signs of that strategy is the role of the Qatar Investment Authority, which has been backing companies involved in core AI infrastructure. In November 2025, QIA joined d-Matrix's $275 million Series C round, supporting a company focused on generative AI inference for data centers. In March 2026, QIA also announced an investment in Ayar Labs, whose co-packaged optics technology is designed to improve the speed and efficiency of next-generation AI computing systems. Together, those moves show QIA is not only targeting AI applications, but also critical enabling technologies deeper in the compute stack. This matters because countries seeking to build sovereign AI capabilities increasingly need more than access to models. They also need exposure to the hardware, networking, and inference technologies that determine performance, cost, and scalability. Qatar's investment pattern suggests it is seeking strategic visibility into those layers while building relationships with companies that could shape future regional deployments. Building the talent base. At the same time, Qatar is putting visible effort into growing the human capital needed to sustain an AI economy. In February 2026, Qatar Foundation and Scale AI launched a partnership focused on capacity-building, innovation activities, and pathways that support Qatar's AI goals, including the exploration of a regional hub for AI development. That initiative reflects a broader recognition that long-term AI competitiveness depends not only on capital and infrastructure, but also on a workforce able to build, train, deploy, and govern advanced systems. That talent agenda is also extending into deep-tech entrepreneurship. QIA and QRDI Council are supporting the launch of DEEP Qatar, an expansion of ESMT Berlin's Institute for Deep Tech Innovation, aimed at helping researchers, startups, and innovators turn scientific advances into scalable businesses. The initiative adds another layer to Qatar's ecosystem strategy by linking research, commercialization, and investment rather than treating them as separate tracks. Expanding local AI infrastructure. Qatar's AI ambitions are also being matched by local infrastructure build-out. Ooredoo launched sovereign AI cloud services in Qatar in 2025 using NVIDIA accelerated computing hosted in local data centers, and in early 2026 its data center arm Syntys expanded its footprint through the acquisition of two facilities in the country. More recently, Oracle and Ooredoo announced a collaboration to deliver sovereign AI and cloud services locally, aimed at helping government and enterprise customers build AI-powered applications while meeting data sovereignty requirements. That local compute layer is especially important for a country trying to serve domestic institutions and regulated sectors while also building regional relevance. Qatar's model appears to be centered on creating in-country capacity first, then using that capacity to support public-sector transformation and private-sector adoption. From strategy to application. On the policy side, Qatar's AI push continues to build on its national AI strategy and the government-led GovAI program, which is designed to accelerate AI adoption across public entities and translate national policy into real-world use cases. Current examples highlighted by MCIT include projects linked to tourism and labor compliance, underscoring that Qatar's AI efforts are not limited to investment announcements or summit-stage visibility but are also feeding into public-service delivery. This application layer is becoming increasingly important. Infrastructure on its own does not create an AI economy unless it is matched by demand from businesses, governments, and startups. Qatar's approach suggests it is trying to build those layers in parallel: backing enabling technologies abroad, expanding local compute capacity, and encouraging domestic institutions to adopt AI in ways that can create lasting demand. A long-term ecosystem play. Rather than forcing immediate localization from every company it backs, Qatar appears to be pursuing a longer-term model. The emphasis is on building relationships across the global AI value chain while preparing the domestic conditions needed for those ties to translate into local economic activity later. That includes training talent, strengthening research commercialization, supporting deep-tech entrepreneurship, and ensuring that sovereign infrastructure is in place when demand scales. As global competition around sovereign AI intensifies, Qatar's strategy is taking shape as an ecosystem play rather than a single bet. Its ambitions now extend from semiconductor-adjacent infrastructure and inference platforms to startup development, education partnerships, and local AI cloud capacity. The result is a broader attempt to secure a role not just as an investor in AI, but as a market where AI technologies can be developed, deployed, and commercialized over time. 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