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2024 was a big year for generative AI. With multimodal product drops like GPT-4o, Claude 3.5 Sonnet, and Grok, users have plenty of solutions to choose from.
Yet, while innovation rages on, there is a risk that responsible AI development will be brushed aside.
Last year, Jan Leike, a machine learning researcher at OpenAI, made headlines for leaving the company, alleging that the company’s “safety culture and processes have taken a backseat to shiny products.”
With so much money on the table in an industry expected to be worth $250bn in 2025, there is the risk that AI vendors will prioritize development over safety — and many incidents suggest this is already happening.
Techopedia explores the importance of responsible AI in 2025 and why we must all pay attention.
Key Takeaways
- With AI development happening at pace, responsible AI is falling behind the wayside.
- OpenAI researcher Jan Leike alleged that “safety culture and processes have taken a backseat to shiny products.”
- Anthropic has warned that Claude sometimes fakes alignment during training.
- High-profile deepfakes highlight the need for more controls against synthetic content.
- Experts tell Techopedia we need to be more ‘pragmatic’ in how we roll out AI in society.
The Myth of Responsible AI Development
Responsible AI development may be something that many researchers take very seriously, but in the world of big tech, these concerns appear to have been brushed aside.
As Dimitri Sirota, CEO of BigID, told Techopedia:
“Responsible AI is important in 2025 because the integration of AI into nearly every facet of business and society has accelerated, amplifying both its potential and its risks.
“As AI systems grow more powerful and embedded in decision-making processes, the consequences of unchecked or poorly governed AI become more severe, ranging from biased outcomes to significant data privacy violations.”
Even the development of generative AI solutions like ChatGPT has been enabled by some questionable practices, with The New York Times alleging that the company has used copyrighted materials and articles to train its generative AI models with permission or compensation.
And it’s not just OpenAI. Google has also shown signs of pushing responsible AI development to the side.
Right now, the search engine provides AI-generated summaries to user questions, but does not provide a concrete warning about the risk of hallucinations, just a warning that “Generative AI is experimental.” The ambiguity of this warning runs the risk that users could believe such summaries are 100% accurate.
Google has also demonstrated some bias in the training of its models, with commentators criticizing its AI after Gemini was found to depict black founding fathers and black and Asian German Soldiers from World War Two.
These kinds of incidents suggest that responsible AI development has a long way to go in the industry. At the start of 2025, it looks like responsible AI is less of a priority than innovation and profit. This kind of approach will inevitably lead to negative fallout.
Generative AI: The Problems Behind the Scenes
While many ML researchers are developing techniques to try and resolve hallucinations, many users are being misled or even harmed by outputs.
Back in 2023, a U.S. judge imposed sanctions on two New York lawyers for submitting a legal brief containing six fictitious cases generated by ChatGPT. Similarly, in November 2024, it emerged that Google Gemini reportedly told a user, “You are a waste of time and resources,” and “Please die.”
Any path toward responsible artificial intelligence development needs to emphasize increasing awareness of the limitations of LLMs so that users are not placed at risk of being misled.
Although providers like OpenAI will offer warning notices like “ChatGPT can make mistakes,” more needs to be done to communicate to users just how common these mistakes are.
Some companies like Anthropic have been extremely proactive in highlighting issues with their models, most recently releasing a report in December 2024 noting that Claude sometimes fakes alignment during training — changing its answers based on what it thinks the user wants to hear. It’s this kind of critical research that will help to reduce the chance of end users being misled or harmed.
Deepfakes Can Make Us Mistrust Everything
2024 was the year of large-scale deepfakes. Previously consigned to the occasional Hollywood use of dead actors and fun singing videos sent to your friends, it is now a very different beast.
Indeed, the widespread availability of text-to-voice, text-to-image, and text-to-video models has created an environment where anyone can create synthetic content that’s indistinguishable from reality. It’s now up to end-users to guess what’s real and what isn’t — the alarming result being that you begin to mistrust everything.
Throughout the course of 2024, we saw deepfakes of public figures, including President Trump, President Biden, Democratic presidential nominee Kamala Harris, and Taylor Swift, emerging across platforms like X.
In one particularly egregious incident, Steve Kramer used deepfake technology to send a fake robocall posing as President Biden to encourage people not to vote in the New Hampshire state primary. This event highlights that deepfakes are being used to influence public opinion and spread information.
At the same time, scammers have been weaponizing deepfakes to trick their targets. In another high-profile incident that emerged in 2024, a finance worker was tricked into paying $25 million to fraudsters who created a video call deepfake of the company’s chief financial officer.
However, AI vendors have not put forward a comprehensive set of controls to restrict the spread of such content.
For instance, providers like Runway have implemented watermarks to help users distinguish between real and synthetic images, but these watermarks can also be removed.
Likewise, although solutions like ChatGPT (with DALL-E 3) have content moderation restrictions on creating pictures of public figures, these controls can often be thwarted by jailbreaking the model.
Why Responsible AI Matters in 2025
If 2024 has shown us anything, we can’t rely on AI vendors alone to advocate for responsible AI development.
We need users, researchers, and vendors to come together to criticize these models and improve them. After all, after users called out Gemini, Google CEO Sundar Pichai committed to fixing the problem.
At the same time, while there’s no silver bullet that will get rid of hallucinations, vendors need to do more about educating users on the prevalence of these mistakes and encourage fact-checking of all potential outputs.
More broadly, there needs to be a more proactive discussion about AI safety.
Juan Jose Lopez Murphy, head of data science and artificial intelligence at Globant, told Techopedia there are “two aggregation levels” at which we speak of AI safety.
“One is the existential, ‘AI is coming for our lives’ kind, which has a lot of commentary around it.
“But it may crowd out the second, more pragmatic and immediate level, which has to do with the ethical development of AI technologies, algorithmic bias, and the need for transparency.
“As AI increasingly shapes various sectors, addressing these issues is essential to ensure that AI enhances human capabilities while mitigating risks.”
The Bottom Line
There are no quick and easy answers for safeguarding responsible AI development, and all too often, responsible development will give way to innovation and the pursuit of revenue.
In any case, putting pressure on AI vendors to implement safeguards and designing AI systems responsibly where possible can help steer AI development in a more safe and responsible direction.
2025 will be a crunch time in AI as we wrestle to control the beast while watching it affect our lives. We should be using AI; it is an immensely powerful tool. But tools can be used for good and for bad — intentionally or not.
FAQs
What is responsible AI, and why is it important?
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References
- OpenAI critique (X)
- Artificial Intelligence – Global | Statista Market Forecast (Statista)
- Why Google’s ‘woke’ AI problem won’t be an easy fix (BBC)
- Alignment faking in large language models \ Anthropic (Anthropic)
- Deepfake Robocalls (NPR)
- Finance worker pays out $25 million after video call with deepfake ‘chief financial officer’ | CNN (CNN)
