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Women in AI: UC Berkeley’s Brandie Nonnecke says investors should push for responsible AI practices

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To give women AI academics and others their well-deserved – and overdue – time in the highlight, TechCrunch is launching a series of interviews specializing in the extraordinary women who’re contributing to the AI ​​revolution. As the AI ​​boom continues, we are going to publish several articles all year long, highlighting key work that usually goes unnoticed. Read more profiles here.

Brandy Nonnecke is the founder and director of the CITRIS Policy Lab on the University of California, Berkeley, which supports interdisciplinary research to reply questions on the role of regulation in promoting innovation. Nonnecke can also be co-director of the Berkeley Center for Law and Technology, where she leads projects on artificial intelligence, platforms and society, and the UC Berkeley AI Policy Hub, an initiative to coach researchers to develop effective AI governance and policy frameworks.

In his spare time, Nonnecke hosts the TecHype video and podcast series, which examines emerging technology policies, regulations and laws, provides insight into the advantages and risks, and identifies strategies for putting technology to good use.

Questions & Answers

Briefly speaking, how did you start in artificial intelligence? What drew you to the sphere?

I actually have been involved in the responsible management of artificial intelligence for almost a decade. My background in technology, public policy and their intersection with social impact drew me to this field. Artificial intelligence is already ubiquitous and has a huge effect on our lives – for higher and for worse. I’m committed to contributing significantly to society’s ability to make use of this technology for good, reasonably than standing on the sidelines.

What work are you most happy with (in AI)?

I’m really happy with two things we achieved. First, the University of California was the primary university to determine a responsible AI policy and governance structure to higher ensure responsible purchasing and use of AI. We take seriously our commitment to serve society in a responsible manner. I had the honour of co-chairing the University of California’s Presidential Working Group on Artificial Intelligence and its subsequent everlasting Council on Artificial Intelligence. In these roles, I used to be capable of gain first-hand experience fascinated by how best to implement our Responsible AI principles to guard our faculty, staff, students and the broader communities we serve. Second, I consider it is amazingly vital that society understands emerging technologies and the actual advantages and risks related to them. We launched TecHype, a video and podcast series that explains emerging technologies and provides guidance for effective technical and policy interventions.

How do you take care of the challenges of the male-dominated tech industry, and by extension, the male-dominated AI industry?

Be curious, persistent and undaunted by imposter syndrome. I consider it is amazingly vital to hunt down mentors who support diversity and inclusion, and to supply the identical support to others entering this field. Building inclusive communities in the tech industry is a robust approach to share experiences, advice and encouragement.

What advice would you give to women wanting to begin working in the AI ​​industry?

For women entering the sphere of artificial intelligence, my advice is threefold: continuously seek knowledge, because artificial intelligence is a rapidly evolving field. Take advantage of networking because contacts will open doors to opportunities and offer invaluable support. Support yourself and others, because your voice is important in shaping an inclusive, equitable future for AI. Remember that your unique perspectives and experiences enrich the sphere and drive innovation.

What are probably the most pressing issues facing artificial intelligence because it evolves?

I consider that some of the pressing issues facing the evolution of artificial intelligence isn’t to be misled by the most recent hype cycles. We’re seeing this now with generative AI. Sure, generative AI is a major advance and may have a huge effect – good and bad. However, there are other types of machine learning in use today that secretly make decisions which have a direct impact on every person’s ability to exercise their rights. Instead of specializing in the most recent marvels of machine learning, it’s more vital that we give attention to how and where machine learning is being applied, no matter its technological prowess.

What issues should AI users pay attention to?

Users of AI should pay attention to issues related to data privacy and security, the potential for bias in AI decision-making, and the importance of transparency in the operation of AI systems and decision-making. Understanding these issues can enable users to demand more accountable and fair AI systems.

What is the very best approach to construct AI responsibly?

Building artificial intelligence responsibly requires taking ethical issues into consideration at every stage of development and implementation. This includes diverse stakeholder engagement, transparent methodologies, bias management strategies and ongoing impact assessments. Prioritizing the general public good and ensuring the event of AI technologies which might be grounded in human rights, equity and inclusion are essential.

How can investors higher promote responsible AI?

This is a vital query! For a protracted time, we never talked explicitly concerning the role of investors. I am unable to express enough how influential investors are! I consider that the claim that “regulation stifles innovation” is overused and infrequently unfaithful. Instead, I strongly consider that smaller firms can gain a late-moment advantage and learn from larger AI firms which might be developing responsible AI practices and guidance from academia, civil society and government. Investors have the ability to shape the direction of the industry, making responsible AI practices a critical factor in investment decisions. This includes supporting initiatives focused on addressing societal challenges through AI, promoting diversity and inclusion in the AI ​​workforce, and advocating for strong governance and technical strategies that help ensure the advantages of AI technologies profit society as a complete.

This article was originally published on : techcrunch.com
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CareYaya enables affordable home care by connecting medical students with seniors

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CareYayaa platform connecting people in need of caregivers with medical students, working to introduce changes within the care industry. The startup, which exhibited as a part of Battlefield 200 on the TechCrunch Disrupt conference, wants to offer affordable at-home support while helping students prepare for a future profession in healthcare.

The startup was founded in 2022 by Neal Shah, who got here up with the thought for the startup from his own experiences as a caregiver for his wife after she contracted cancer and various other ailments. At the time, Shah was a partner in a hedge fund and needed to close his fund to function his child’s full-time caregiver for 2 years.

To provide extra care for his wife, Shah hired students studying health care to be his wife’s caregivers. Shah learned that other families were informally doing the identical, posting fliers on local campuses asking them to search out someone qualified to care for his or her loved one.

“I thought, wouldn’t it be nice to just build a formal system for them where you don’t have to go to the local nursing school or the local undergraduate campus and send out flyers,” Shah told TechCrunch. “That’s what I used to be doing. So we thought should you could make it formal through a technology platform, you may make a huge impact.

Fast forward to 2024, and the platform currently has over 25,000 students from multiple schools including Duke University, Stanford, UC Berkeley, San Jose State, the University of Texas at Austin, and more.

Image credits:CareYaya

CareYaya conducts background checks on students who want to affix the platform after which conducts video interviews with them. On the user side, people can join the platform after which detail the sort of care their loved one needs. CareYaya then matches students with families, whether for one-time sessions or ongoing care. After the primary session, each parties can submit rankings.

The startup claims it might help families save 1000’s of dollars on recurring elder care. During home care costs average In the US, $35 per hourCareYaya charges between $17 and $20 per hour.

Because student caregivers are tech-savvy, CareYaya equips them with AI-powered technology to acknowledge and track disease progression in Alzheimer’s and dementia patients. The company recently launched an LLM (Large Language Model) that integrates with smart glasses to gather visual data to assist students provide higher real-time assistance and conduct early screening for dementia.

As for the long run, CareYaya is trying to expand beyond the US as people in places like Canada, Australia and the UK have shown interest within the platform.

This article was originally published on : techcrunch.com
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SpaceX wants to test refueling spacecraft in space early next year

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SpaceX will attempt to transfer fuel from one orbiting spacecraft to one other as early as March next year, a technical milestone that may pave the way in which for an uncrewed demonstration of the spacecraft on the Moon, a NASA official said this week.

Much has been said about Starship’s potential to transform the industrial space industry, but NASA can also be losing hope that the vehicle will return humans to the Moon under the Artemis program. The space agency has awarded the corporate a $4.05 billion contract for 2 human Starship vehicles, with the upper stage (also called Starship) landing astronauts on the lunar surface for the primary time because the Apollo era. A crewed landing is currently scheduled for September 2026.

Kent Chojnacki, deputy program manager for NASA’s Human Landing System (HLS) program, provided more details on how closely the agency will work with the space company on this critical mission in an interview with Spaceflight Now. It will come as no surprise that NASA is paying close attention to the Starship test campaign, which has seen five launches thus far.

SpaceX made history in its latest test on Oct. 13 when it first managed to catch a super-heavy rocket booster in mid-air using “sticks” attached to the launch tower.

“Every time it comes to (launch), we learn a lot,” Chojnacki said.

Chojnacki’s work history includes quite a few roles in the Space Launch System (SLS) program, which oversees the event of the large rocket of the identical name being built by a handful of traditional space-first aircraft. The first SLS rocket launched the Artemis I mission in December 2023, and future rockets will launch additional missions under the Artemis program. However, no a part of the rocket is reusable, which is why NASA spends greater than $2 billion on each launch vehicle.

The first contracts under the SLS program were awarded over ten years ago as a part of the so-called a cost-plus model, meaning NASA pays a base amount plus expenses. (This variety of contract has been heavily criticized for encouraging long development schedules and high expenses.) In contrast, HLS contracts are “fixed price” – so SpaceX receives a one-time payment of $2.99 ​​billion, provided certain milestones are met.

Chojnacki said NASA has taken very different approaches to the HLS and SLS programs, even outside of the contracting model.

“SLS was a very traditional NASA program. NASA defined a very stringent set of requirements and dictated the fuel supplies, dictated everything to the various elements. They flowed downwards. These were cost-effective programs where aerospace companies responded and we worked in a very traditional way,” he said. “Moving to HLS, we’re doing a whole lot of moving parts without delay. Currently, SpaceX’s first landing contract includes 27 system requirements. Twenty-seven and we tried to be as relaxed as possible.

Under the SpaceX contract, they have to pass mandatory design reviews, but SpaceX may offer additional milestones as a part of the payment. One of the necessities required by SpaceX is an indication of ship-to-ship propellant transfer. These tests are scheduled to start around March 2025 and end in the summer, Chojnacki said.

“This could be the primary time this has been demonstrated on this scale, so it’s an enormous constructing block. And when you try this, you have really opened up the door to moving huge amounts of cargo and charge beyond the globe of the Earth. If you manage to have a spacecraft with a propellant unit, that can be the next step towards uncrewed demonstrations.

In addition to testing, Starship’s next major review can be the Critical Design Review (CDR) in summer 2025, when NASA will certify that the corporate has met all 27 system requirements. Chojnacki said NASA astronauts also meet with SpaceX once a month to provide information concerning the interior of Starship. The company is constructing mock-ups of the crew cabin, including the sleeping area and laboratory, in Boca Chica. NASA anticipates receiving a design update this month before it during next year’s CDR.

That’s not the one place NASA shared its input: it also provided feedback on some facets of the rocket’s design, similar to the vehicle’s cryogenic components, and in addition performed some tests on thermal plates that help keep the temperature of cryogenic fuels low.

If all goes according to plan, SpaceX will send astronauts to the Moon in September 2026.

“It’s definitely a date we’re working towards. We haven’t any known roadblocks. We have some things that need to be demonstrated for the primary time and we’ve a plan on how to exhibit them.

This article was originally published on : techcrunch.com
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Microsoft and A16Z are putting aside their differences and joining hands in protest against artificial intelligence regulations

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Image of a computer, phone and clock on a desk tied in red tape.

The two biggest forces in two deeply intertwined tech ecosystems – large incumbents and startups – have taken a break from counting money and together they demand this from the federal government to stop even considering regulations that might affect their financial interests or, as they prefer to call it, innovation.

“Our two companies may not agree on everything, but it’s not about our differences,” writes this group with very different perspectives and interests: A16Z founders, partners Marc Andreessen and Ben Horowitz, and Microsoft CEO Satya Nadella and president/director legal affairs Brad Kowal. A very cross-sectional gathering, representing each big business and big money.

But they are supposedly taking care of little boys. That is, all the businesses that may be impacted by this latest try to abuse the regulations: SB 1047.

Imagine being charged a fee for improperly disclosing an open model! A16Z General Partner Anjney Midha he called it a “regressive tax” on startups and a “blatant regulatory capture” by Big Tech firms that, unlike Midha and his impoverished colleagues, could afford the lawyers needed to comply with the regulations.

Except that was all disinformation spread by Andreessen Horowitz and other wealthy interests who actually stood to suffer as supporters of billion-dollar enterprises. In fact, small models and startups would only be barely affected since the proposed law specifically protected them.

It’s strange that the identical form of targeted carve-out for “Little Tech” that Horowitz and Andreessen routinely advocate for was distorted and minimized by the lobbying campaign they and others waged against SB 1047. (In an interview with the bill’s sponsor , California State Senator Scott Wiener talked about this whole thing recently on Disrupt.)

This bill had its problems, but its opposition greatly exaggerated compliance costs and didn’t significantly substantiate claims that it will chill or burden startups.

It’s a part of a longtime pattern in which Big Tech – to which, despite their stance, Andreessen and Horowitz are closely related – operates on the state level, where it could possibly win (as with SB 1047), while asking for federal solutions that it knows will won’t ever come, or which can have no teeth because of partisan bickering and congressional ineptitude on technical issues.

This joint statement of “political opportunity” is the second a part of the sport: After torpedoing SB 1047, they will say they did it solely to support federal policy. Never mind that we’re still waiting for a federal privacy law that tech firms have been pushing for a decade while fighting state laws.

What policies do they support? “A different responsible market approach”, in other words: down with our money, Uncle Sam.

Regulations needs to be based on a “science-based and standards-based approach, recognizing regulatory frameworks that focus on the use and misuse of technology” and should “focus on the risk of bad actors exploiting artificial intelligence.” This signifies that we must always not introduce proactive regulation, but quite reactive penalties when criminals use unregulated products for criminal purposes. This approach has worked great in this whole FTX situation, so I understand why they support it.

“The regulation should only be implemented if the benefits outweigh the costs.” It would take 1000’s of words to clarify all of the ways this idea expressed in this context is funny. But they are principally suggesting that the fox needs to be included on the henhouse planning committee.

Regulators should “allow developers and startups the flexibility to choose AI models to use wherever they build solutions, and not tilt the playing field in favor of any one platform.” This suggests that there may be some agenda requiring permission to make use of one model or one other. Since this is just not the case, it’s a straw man.

Here is a lengthy quote that I have to quote in full:

The right to education: Copyright goals to advertise the progress of science and the applied arts by extending protection to publishers and authors to encourage them to make recent works and knowledge available to the general public, but not on the expense of society’s right to learn from those works. Copyright law mustn’t be co-opted to suggest that machines needs to be prevented from using data – the premise of artificial intelligence – to learn in the identical way as humans. Unprotected knowledge and facts, whether or not contained in protected subject material, should remain free and accessible.

To be clear, the clear statement here is that software operated by billion-dollar corporations has the “right” to access any data since it should give you the chance to learn from it “in the same way as humans.”

First of all, no. These systems are not like people; they generate data in their training data that mimics human activity. These are complex statistical projection programs with a natural language interface. They haven’t any more “right” to any document or fact than Excel.

Second, the concept that “facts” – by which they mean “intellectual property” – are the one thing these systems are interested in, and that some type of fact-gathering cabal is working to forestall them, is an artificial narrative we have seen before. Perplexity made the “facts belong to everyone” argument in its public response to a lawsuit alleging systematic content theft, and its CEO Aravind Srinivas repeated that mistake to me on stage at Disrupt, as in the event that they were being sued for knowing tidbits just like the Earth’s distance from the Moon.

While this is just not the place to totally discuss this particular straw man argument, let me simply indicate that while facts are indeed free agents, there are real costs to how they are created – say, through original reporting and scientific research. This is why copyright and patent systems exist: not to forestall the wide sharing and use of mental property, but to encourage its creation by ensuring that it could possibly be assigned real value.

Copyright law is much from perfect and is more likely to be abused as often as used. However, this is just not “co-opted to suggest that machines should be prevented from using data” – it’s used to be sure that bad actors don’t bypass the worth systems we’ve got built around mental property.

This is a fairly clear query: let’s allow the systems we own, operate and take advantage of to freely use the worthwhile work of others without compensation. To be fair, this part is “in the same way as people” because people design, run and implement these systems, and these people don’t desire to pay for something they do not have to, and they don’t desire to. I don’t desire regulations to alter that .

There are many other recommendations in this small policy document, which were little question covered in greater detail in the versions sent on to lawmakers and regulators through official lobbying channels.

Some of the ideas are undoubtedly good, if slightly selfish: “fund digital literacy programs that help people understand how to use artificial intelligence tools to create and access information.” Good! Of course, the authors invest heavily in these tools. Support “Open Data Commons – collections of accessible data managed in the public interest.” Great! “Examine procurement practices to enable more startups to sell technology to the government.” Excellent!

But these more general, positive recommendations are something the industry sees yearly: invest in public resources and speed up government processes. These tasty but irrelevant suggestions are merely tools for the more vital ones I described above.

Ben Horowitz, Brad Smith, Marc Andreessen and Satya Nadella want the federal government to step back from regulating this lucrative recent development, let industry resolve which regulations are value compromising, and invalidate copyright laws in a way that kind of acts as a blanket reprieve for illegal or unethical practices that many imagine have enabled the rapid development of artificial intelligence. These are principles that are vital to them, whether children are acquiring digital skills or not.

This article was originally published on : techcrunch.com
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