Category Archives: Deep Mind
The ethics of advanced AI assistants – Google DeepMind
Responsibility & Safety
Iason Gabriel and Arianna Manzini
Exploring the promise and risks of a future with more capable AI
Imagine a future where we interact regularly with a range of advanced artificial intelligence (AI) assistants and where millions of assistants interact with each other on our behalf. These experiences and interactions may soon become part of our everyday reality.
General-purpose foundation models are paving the way for increasingly advanced AI assistants. Capable of planning and performing a wide range of actions in line with a persons aims, they could add immense value to peoples lives and to society, serving as creative partners, research analysts, educational tutors, life planners and more.
They could also bring about a new phase of human interaction with AI. This is why its so important to think proactively about what this world could look like, and to help steer responsible decision-making and beneficial outcomes ahead of time.
Our new paper is the first systematic treatment of the ethical and societal questions that advanced AI assistants raise for users, developers and the societies theyre integrated into, and provides significant new insights into the potential impact of this technology.
We cover topics such as value alignment, safety and misuse, the impact on the economy, the environment, the information sphere, access and opportunity and more.
This is the result of one of our largest ethics foresight projects to date. Bringing together a wide range of experts, we examined and mapped the new technical and moral landscape of a future populated by AI assistants, and characterized the opportunities and risks society might face. Here we outline some of our key takeaways.
Illustration of the potential for AI assistants to impact research, education, creative tasks and planning.
Advanced AI assistants could have a profound impact on users and society, and be integrated into most aspects of peoples lives. For example, people may ask them to book holidays, manage social time or perform other life tasks. If deployed at scale, AI assistants could impact the way people approach work, education, creative projects, hobbies and social interaction.
Over time, AI assistants could also influence the goals people pursue and their path of personal development through the information and advice assistants give and the actions they take. Ultimately, this raises important questions about how people interact with this technology and how it can best support their goals and aspirations.
Illustration showing that AI assistants should be able to understand human preferences and values.
AI assistants will likely have a significant level of autonomy for planning and performing sequences of tasks across a range of domains. Because of this, AI assistants present novel challenges around safety, alignment and misuse.
With more autonomy comes greater risk of accidents caused by unclear or misinterpreted instructions, and greater risk of assistants taking actions that are misaligned with the users values and interests.
More autonomous AI assistants may also enable high-impact forms of misuse, like spreading misinformation or engaging in cyber attacks. To address these potential risks, we argue that limits must be set on this technology, and that the values of advanced AI assistants must better align to human values and be compatible with wider societal ideals and standards.
Illustration of an AI assistant and a person communicating in a human-like way.
Able to fluidly communicate using natural language, the written output and voices of advanced AI assistants may become hard to distinguish from those of humans.
This development opens up a complex set of questions around trust, privacy, anthropomorphism and appropriate human relationships with AI: How can we make sure users can reliably identify AI assistants and stay in control of their interactions with them? What can be done to ensure users arent unduly influenced or misled over time?
Safeguards, such as those around privacy, need to be put in place to address these risks. Importantly, peoples relationships with AI assistants must preserve the users autonomy, support their ability to flourish and not rely on emotional or material dependence.
Illustration of how interactions between AI assistants and people will create different network effects.
If this technology becomes widely available and deployed at scale, advanced AI assistants will need to interact with each other, with users and non-users alike. To help avoid collective action problems, these assistants must be able to cooperate successfully.
For example, thousands of assistants might try to book the same service for their users at the same time potentially crashing the system. In an ideal scenario, these AI assistants would instead coordinate on behalf of human users and the service providers involved to discover common ground that better meets different peoples preferences and needs.
Given how useful this technology may become, its also important that no one is excluded. AI assistants should be broadly accessible and designed with the needs of different users and non-users in mind.
Illustration of how evaluations on many levels are important for understanding AI assistants.
AI assistants could display novel capabilities and use tools in new ways that are challenging to foresee, making it hard to anticipate the risks associated with their deployment. To help manage such risks, we need to engage in foresight practices that are based on comprehensive tests and evaluations.
Our previous research on evaluating social and ethical risks from generative AI identified some of the gaps in traditional model evaluation methods and we encourage much more research in this space.
For instance, comprehensive evaluations that address the effects of both human-computer interactions and the wider effects on society could help researchers understand how AI assistants interact with users, non-users and society as part of a broader network. In turn, these insights could inform better mitigations and responsible decision-making.
We may be facing a new era of technological and societal transformation inspired by the development of advanced AI assistants. The choices we make today, as researchers, developers, policymakers and members of the public will guide how this technology develops and is deployed across society.
We hope that our paper will function as a springboard for further coordination and cooperation to collectively shape the kind of beneficial AI assistants wed all like to see in the world.
Paper authors: Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomaev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sbastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael, Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agera y Arcas, William Isaac and James Manyika.
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The ethics of advanced AI assistants - Google DeepMind
Google Consolidates AI-Building Teams Into DeepMind – PYMNTS.com
Google is consolidating the teams that focus on building artificial intelligence (AI) models acrossGoogle ResearchandGoogle DeepMind.
All this work will now be done within Google DeepMind,Sundar Pichai, CEO of Google and Alphabet, said in anote to employeesposted on the companys website Thursday (April 18).
Pichai said in the note that this move will scale our capacity to deliver capable AI for our users, partners and customers.
It will simplify development by concentrating compute-intensive model building in one place, establish single access points for those looking to take these models and build generative AI applications, and give Google Research a clear and distinct mandate to invest in three key areas: computing systems, foundational machine learning and algorithms, and applied science and society, according to the note.
This move comes a year after the company created Google DeepMind by bringing together Google Brain, DeepMind and other researchers focused on AI systems, per the note. This group developed the companysGeminimodels.
The letter also announced changes to the way Googles Responsible AI teams work.
Those in Research have been moved to DeepMind, other responsibility teams have been moved to the central Trust and Safety team, and the company is increasing investment in testing AI-powered features for vulnerabilities, the note said.
These changes continue the work weve done over the past year to simplify our structure and improve velocity and execution such as bringing together the Brain team in Google Research with teams in DeepMind, which helped accelerate our Gemini models; unifying our ML infrastructure and ML developer teams to enable faster decisions, smarter compute allocation and a better customer experience; and bringing our Search teams under one leader, Pichai said in the note.
It was reported Tuesday (April 16) that Googlesspending on AIwill surpass $100 billion.
When asked at a conference about reports that Google rivals Microsoft and OpenAI plan to spend $100 billion on an AI supercomputer known as Stargate, DeepMind CEODemis Hassabissaid: We dont talk about our specific numbers, but I think were investing more than that over time.
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Google Consolidates AI-Building Teams Into DeepMind - PYMNTS.com
Google will outpace Microsoft in AI investment, DeepMind CEO says – TNW
We have all been guilty of falling under the foundation model spell of the past year-and-a-half, initiated by OpenAIs unveiling of ChatGPT to the public.
But it is not only where large language models (LLMs) such as GPT-4 are concerned that incredible progress has been made in the field of artificial intelligence. And one company has been behind more impressive milestones than most DeepMind, acquired by Google in 2014 for a reported400mn to 650mn.
Speaking at the TED 40th anniversary conference in Vancouver, Canada, on Monday, DeepMinds CEO and head of Googles entire AI R&D efforts, Demis Hassabis, confirmed that Google has no intention of slowing down investment in the technology. Quite the opposite.
While Hassabis said Google does not talk about specific numbers, the company will surpass the $100 billion that Microsoft and OpenAI plan to invest in their Stargate AI supercomputer over the coming years.
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We are investing more than that over time, and that is one of the reasons we teamed up with Google, Hassabis said. We knew that in order to get to AGI, we would need a lot of compute and Google had, and still has, the most computers.
While this sounds like the perfect scenario for an artificial intelligence arms race that could lead to rolling the dice on things like reinforcement learning and AI safety, Hassabis reiterated that this must be avoided.
According to the DeepMind CEO, this is especially important as we come nearer to achieving artificial general intelligence AI that can match or surpass human cognitive abilities such as reasoning, planning, and remembering.
This technology is still relatively nascent, and so its probably ok what is happening at the moment, Hassabis said. But as we get closer to AGI we need to start thinking as a society about the types of architectures that get built. The good news is that most of these scientists who are working on this, we know each other quite well, we talk to each other a lot at conferences, Hassabis stated. (Raise your hand if you are only mildly reassured by this particular piece of information.)
Hassabis further added that learning to build safe AGI architectures is a kind of bottleneck that humanity needs to get through, in order to emerge on the other side to a flourishing of many different types of systems that have emerged from the initial ones with mathematical or practical guarantees around what they do.
The responsibility for preventing a runaway race dynamic from happening, Hassabis believes, rests not only with AI industry labs, but many other parts of society: governments, civil society, and academia. If we get this right, we could be in this incredible new era of radical abundance, curing all diseases, spreading consciousness to the stars, and maximum human flourishing.
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Google will outpace Microsoft in AI investment, DeepMind CEO says - TNW
Tech Giant Google Reveals Plans To Merge Its AI Research And DeepMind Divisions – Tech Business News
In a statement on Thursday, Google disclosed intentions to unite its Research and DeepMind divisions, aligning teams dedicated to crafting AI models.
The search engine giant will consolidate teams that focus on building artificial intelligence models across its Research and DeepMind divisions in its latest push to develop its AI portfolio. The move comes amid growing global concerns about AI safety and increasing calls for regulation of the technology.
Gemini, unveiled last year, boasts capabilities to process various data formats, including video, audio, and text. However, Google faced criticism following inaccuracies in historical image generation, prompting a pause in certain image generation functionalities.
While the rollout of Gemini helped boost Alphabets share price, it came under fire after inaccuracies in some historical image generation depiction.
Rick Osterloh, previously overseeing Googles hardware efforts, will lead the Platforms and Devices team, emphasising the pivotal role of AI in shaping user experiences.
Osterloh highlights the integration of hardware, software, and AI as crucial for transformative innovations, citing examples such as Pixels camera technology.
Google emphasises that the consolidation isnt indicative of a shift away from its dedication to the broader Android ecosystem. Instead, it highlights the companys amplified emphasis on integrating AI across its platforms.
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Tech Giant Google Reveals Plans To Merge Its AI Research And DeepMind Divisions - Tech Business News
Sundar Pichai on merging Android and Pixel teams, Google DeepMind, more – 9to5Google
Sundar Pichai is out with an internal email today detailing the big Platforms & Devices reorganization of Android, Chrome and Pixel, as well as other company-wide changes.
To truly drive computing forward, we need to do it at the intersection of hardware, software and AI. So we are formalizing the collaboration between DSPA and P&E and bringing the teams together in a new PA called Platforms & Devices.
The Alphabet/Google CEO says this merger will result in higher quality products and experiences for our users and partners. Specifically, it will turbocharge the Android and Chrome ecosystems and bring the best innovations to partners faster, with Circle to Search for Samsung cited as an example.
This should speed up decision-making internally.It follows the hardware division in January switching to a functional organization model where, for example, there is one team for hardware engineering across Pixel, Nest, and Fitbit.
Meanwhile, there are other AI changes today. All compute-intensive model building now takes place within Google DeepMind. This gives other teams within Google single access points for tak[ing] these models and build[ing] generative AI applications.
Meanwhile, Googles Responsible AI teams are moving from Research to DeepMind to be closer to where the models are built and scaled.
Were standardizing launch requirements for AI-powered features and increasing investments in red team testing for vulnerabilities and broader evaluations to help ensure responses are accurate and responsive to our users prompts.
Meanwhile, Google Research is getting a clear and distinct mandate to continue investing in foundational and applied computer science research in three key areas:
Fundamental computer science research is in our DNA and we have some of the worlds best computer scientists. We simply would not be the company we are today without the researchers who developed the foundations on which all Googles products are built and are now inventing the foundations for our future.
Pichai ends on a mission first note:
We have a duty to be an objective and trusted provider of information that serves all of our users globally. When we come to work, our goal is to organize the worlds information and make it universally accessible and useful. That supersedes everything else and I expect us to act with a focus that reflects that.
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Sundar Pichai on merging Android and Pixel teams, Google DeepMind, more - 9to5Google
Google merges DeepMind and Research teams in latest AI push – Verdict
Google announced on Thursday (18 April) that it will be merging teams that focus on building AI models across its Research and DeepMind divisions, in the latest move by the company to catch up in the GenAI race.
Google will be moving its Responsible AI teams from its Research department to DeepMind in order for it to be closer to where its AI models are being built, according to the company.The Responsible AI team focuses on safe AI development.
The move comes as concern about AI safety grows and global lawmakers increasingly seek effective ways to regulate the rapidly growing technology.
At the start of April, the UK and US governments signed a memorandum of understanding in a partnership to tackle AI safety and ethics.
The two countries previously pledged to work together on AI safety during the UKs AI Safety Summit in November 2023 at Bletchley Park.
Under the partnership, the UKs AI Safety Institute will share its research with the US. The countries have also committed to partnering with other countries on AI safety.
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The UKs Science, Technology and Innovation Secretary, Michelle Donelan, described the partnership as a landmark moment in AI development.
We have always been clear that ensuring the safe development of AI is a shared global issue, she said. Only by working together can we address the technologys risks head on and harness its enormous potential to help us all live easier and healthier lives.
GlobalData forecasts that the overall AI market will be worth $909bn (712.25bn) by 2030, registering a compound annual growth rate (GAGR) of 35% between 2022 and 2030.
In the GenAI space, revenues are expected to grow from $1.8bn in 2022 to $33bn in 2027 at a CAGR of 80%.
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Google merges DeepMind and Research teams in latest AI push - Verdict
DeepMind CEO Says Google Will Spend More Than $100 Billion on AI – Bloomberg
The chief of Googles AI business said that over time the company will spend more than $100 billion developing artificial intelligence technology another sign of the investing arms race that has gripped Silicon Valley.
Google DeepMind Chief Executive Officer Demis Hassabis was asked at a TED conference in Vancouver on Monday about a potential $100 billion supercomputer dubbed Stargate, being planned by Microsoft Corp. and OpenAI, according to a report in the Information last month.
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DeepMind CEO Says Google Will Spend More Than $100 Billion on AI - Bloomberg
Google will spend more than $100 billion on AI, exec says – Quartz
After comparing the billions of dollars going into AI development to crypto hype, Googles AI chief executive said Monday the company will spend over $100 billion over time to develop AI technology.
ChatGPT requires 15 times more energy than a traditional web search, says Arm exec
Demis Hassabis, chief executive of Google DeepMind, talked about the tech giants investment into AI during a TED conference in Vancouver on Monday, where he was asked about OpenAIs and Microsofts reported plans for a U.S.-based data center referred to as Stargate, Bloomberg reported. The data center would house a supercomputer made up of millions of AI chips, and could cost up to $100 billion, The Information reported, citing unnamed sources.
We dont talk about our specific numbers, but I think were investing more than that over time, Hassabis said in response to the question about Stargate. He didnt offer further details on Googles spending plans, Bloomberg reported. Hassabis, who co-founded AI startup DeepMind in 2010 before it was acquired by Google in 2014, reportedly added that Google parent Alphabet has better computing power than its rivals, including Microsoft.
Thats one of the reasons we teamed up with Google back in 2014, is we knew that in order to get to AGI we would need a lot of compute, Hassabis said. Artificial general intelligence (AGI) is the point at which AI reaches human-level knowledge across a range of tasks. Google had and still has the most computers, Hassabis said.
In March, Hassabis told the Financial Times that the billions of dollars being poured into AI is reminiscent of crypto hype, and is taking attention away from the phenomenal science and research behind its development.
The investment into AI brings with it a whole attendant bunch of hype and maybe some grifting, he said, comparing it to crypto and similar areas, adding that the sentiment has now spilled over into AI, which I think is a bit unfortunate.
However, Hassabis said he thinks the industry is only scratching the surface of what is possible. Were at the beginning, maybe, of a new golden era of scientific discovery, a new Renaissance, he said.
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Google will spend more than $100 billion on AI, exec says - Quartz
DeepMind Head: Google AI Spending Could Exceed $100 Billion – PYMNTS.com
Googles top AI executive says the companys spending on the technology will surpass $100 billion.
While speaking Monday (April 15) at a TED Conference in Vancouver, DeepMind CEO Demis Hassabis was asked about recent reports of Microsoft and OpenAIs planned artificial intelligence (AI) supercomputer known as Stargate,said to cost $100 billion.
We dont talk about our specific numbers, but I think were investing more than that over time, said Hassabis, whose comments were reported by Bloomberg News.
Hassabis, who co-founded DeepMind in 2010 before it was bought by Google four years later, did not offer further details on the potential AI investment, the report said. He also told the audience Googles computer power surpasses that of competitors like Microsoft.
Thats one of the reasons we teamed up with Google back in 2014, is we knew that in order to get to AGI we would need a lot of compute, he said, referring to artificial general intelligence, or AI that surpasses the intelligence of humans.
Thats whats transpired, he said. And Google had and still has the most computers.
Hassabis added that the massive interest kicked off by OpenAIs ChatGPT AI model demonstrated the public was ready for the technology, even if AI systems are still prone to errors.
As PYMNTS wrote earlier this month, the Stargate project spotlights the increasing role of AI in fueling innovation and determining the future of commerce. Experts believe that as tech giants invest heavily in AI research and infrastructure, the creation of sophisticated AI systems could revolutionize areas like personalized marketing and supply chain optimization.
It is important to consider the potential impact on jobs and the workforce, Jiahao Sun, founder and CEO at FLock.io, a platform for decentralized AI models, said in an interview with PYMNTS.
As AI becomes more capable in multimodal and integrated into commerce, it may automate industries that currently cannot easily be transferred into a chatbot interface, such as manufacturing, healthcare, sports coaching, etc.
Microsoft and OpenAIs $100 billion project could make AI chips more scarce, leading to more price spikes and leaving more businesses and governments behind due to limited access to hardware, CEO and co-founder of AI company NeuReality Moshe Tanachtold PYMNTS, while adding that projects like Stargate will drive commerce forward in the short term.
The installed hardware will fuel more AI projects, features and use cases, leading Microsoft to offer it at consumable prices, driving innovation on the consumer side with secondary use cases built on this accessible AI technology, Tanach said.
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DeepMind Head: Google AI Spending Could Exceed $100 Billion - PYMNTS.com