#ethical-ai

#ethical-ai

The question for the coming year, then, is no longer whether AI will transform your organization, it's whether your leadership team will guide that transformation thoughtfully or let it happen haphazardly, tool by tool and team by team. I have spent much of the past year working with my research team and industry partners to think through the most pressing challenges organizations face as they implement AI at scale. Drawing on this work, I have identified seven key priorities for leaders preparing for 2026.

Enter Nano Banana Pro, Google's new AI-powered image generation tool that's redefining the boundaries of creativity. Built on the robust Gemini 3 Pro foundation, this tool doesn't just generate images; it interprets, reasons, and aligns visuals with cultural nuances and current events. Imagine crafting a marketing campaign that seamlessly integrates trending themes or designing educational materials that feel as dynamic as the lessons they support.

There is a persistent myth of objectivity around AI, perhaps because people assume that once the systems are deployed, they can function without any human intervention. In reality, developers constantly tweak and refine algorithms with subjective decisions about which results are more relevant or appropriate. Moreover, the immense corpus of data that machine learning models train on can also be polluted.

When Val Vavilov co-founded his Bitcoin mining company, Bitfury, in 2011, the original cryptocurrency was worth less than $30, a sliver of its roughly $91,000 price today. Since then, Bitfury's mining ventures spun off into two Nasdaq listed companies whose combined worth tops $9 billion, while also launching two companies that offer AI infrastructure. Bitfury's next step? It wants to use its money to invest in the next crop of ethical tech innovators.

From reproductive rights to climate change to Big Tech, The Independent is on the ground when the story is developing. Whether it's investigating the financials of Elon Musk's pro-Trump PAC or producing our latest documentary, 'The A Word', which shines a light on the American women fighting for reproductive rights, we know how important it is to parse out the facts from the messaging.

Synthetic speech is no longer the stuff of science fiction. From audiobooks and dubbing to gaming and avatars, AI-generated voice is breaking into the mainstream - and Mati Staniszewski, CEO and co-founder of ElevenLabs, is helping lead the charge. At TechCrunch Disrupt 2025, he'll take the stage to talk about what it takes to make voice AI truly human. Shaping the future of sound

Not all AI tools are created equal. Some excel at thoughtful, human-like conversations. Others at digging up real-time information in seconds. But when choosing between Anthropic's Claude and Perplexity's AI search engine, you're not just comparing features, you're deciding how to work smarter. Do you need an AI assistant that thinks before it speaks? Or one that gets straight to the facts, speedily, and with its sources cited? The difference isn't subtle, and the impact on your daily workflow can be game-changing.

Moonvalley has raised a total of $154 million in funding, with $84 million coming from its most recent investment round led by General Catalyst and supported by notable Hollywood entities like CAA and Comcast Ventures.

Today, most AI is being built on blind faith inside of black boxes. It requires users to have on unquestioning belief in something neither transparent nor understandable.

Bryn Mooser and Natasha Lyonne co-founded Asteria to leverage generative AI for filmmaking in a way they describe as 'ethical,' despite facing industry backlash.

The CC signals project proposes a solution that balances data sharing with governance, allowing dataset holders to specify AI usage while fostering openness in the digital landscape.

Konwinski described the Laude Institute's mission as 'built by and for computer science researchers ... We exist to catalyze work that doesn't just push the field forward but guides it towards more beneficial outcomes.'

The alarming reality is that AI-driven learning can perpetuate biases present in data sources, leading to unfair treatment and unequal opportunities for diverse learners.

The goal of the Ethical AI Guidebook is to spark a mindset shift-encouraging content creators, agencies, and AI developers to make inclusivity a core part of how they generate and use imagery.