One of the motivations for founding Creative Commons (CC) was offering more choices for people who wish to share their works openly. Through engagement with a wide variety of stakeholders, we heard frustrations with the “all or nothing” choices they seemed to face with copyright. Instead they wanted to let the public share and reuse their works in some ways but not others. We also were motivated to create the CC licenses to support people — artists, technology developers, archivists, researchers, and more — who wished to re-use creative material with clear, easy-to-understand permissions.

What’s more, our engagement revealed that people were motivated to share not merely to serve their own individual interests, but rather because of a sense of societal interest. Many wanted to support and expand the body of knowledge and creativity that people could access and build upon — that is, the commons. Creativity depends on a thriving commons, and expanding choice was a means to that end.

Similar themes came through in our community consultations on generative artificial intelligence (AI*). Obviously, the details of AI and technology in society in 2023 are different from 2002. But the challenges of an all-or-nothing system where works are either open to all uses, including AI training, or entirely closed, are a through-line. So, too, is the desire to do so in a way that supports creativity, collaboration, and the commons.

One option that was continually raised was preference signaling: a way of making requests about some uses, not enforceable through the licenses, but an indication of the creators’ wishes. We agree that this is an important area of exploration. Preference signals raise a number of tricky questions, including how to ensure they are a part of a comprehensive approach to supporting a thriving commons — as opposed to merely a way to limit particular ways people build on existing works, and whether that approach is compatible with the intent of open licensing. At the same time, we do see potential for them to help facilitate better sharing.

What We Learned: Broad Stakeholder Interest in Preference Signals

In our recent posts about our community consultations on generative AI, we have highlighted the wide range of views in our community about generative AI.

Some people are using generative AI to create new works. Others believe it will interfere with their ability to create, share, and earn compensation, and they object to current ways AI is trained on their works without express permission.

While many artists and content creators want clearer ways to signal their preferences for use of their works to train generative AI, their preferences vary. Between the poles of “all” and “nothing,” there were gradations based on how generative AI was used specifically. For instance, they varied based on whether generative AI is used

• to edit a new creative work (similar to the way one might use Photoshop or another editing program to alter an image),
• to create content in the same category of the works it was trained on (i.e., using pictures to generate new pictures),
• to mimic a particular person or replace their work generally, or
• to mimic a particular person and replace their work to commercially pass themselves off as the artist (as opposed to doing a non-commercial homage, or a parody).

Views also varied based on who created and used the AI — whether researchers, nonprofits, or companies, for instance.

Many technology developers and users of AI systems also shared interest in defining better ways to respect creators’ wishes. Put simply, if they could get a clear signal of the creators’ intent with respect to AI training, then they would readily follow it. While they expressed concerns about over-broad requirements, the issue was not all-or-nothing.

Preference Signals: An Ambiguous Relationship to a Thriving Commons

While there was broad interest in better preference signals, there was no clear consensus on how to put them into practice. In fact, there is some tension and some ambiguity when it comes to how these signals could impact the commons.

For example, people brought up how generative AI may impact publishing on the Web. For some, concerns about AI training meant that they would no longer be sharing their works publicly on the Web. Similarly, some were specifically concerned about how this would impact openly licensed content and public interest initiatives; if people can use ChatGPT to get answers gleaned from Wikipedia without ever visiting Wikipedia, will Wikipedia’s commons of information continue to be sustainable?

From this vantage point, the introduction of preference signals could be seen as a way to sustain and support sharing of material that might otherwise not be shared, allowing new ways to reconcile these tensions.

On the other hand, if preference signals are broadly deployed just to limit this use, it could be a net loss for the commons. These signals may be used in a way that is overly limiting to expression — such as limiting the ability to create art that is inspired by a particular artist or genre, or the ability to get answers from AI systems that draw upon significant areas of human knowledge.

Additionally, CC licenses have resisted restrictions on use, in the same manner as open source software licenses. Such restrictions are often so broad that they cut off many valuable, pro-commons uses in addition to the undesirable uses; generally the possibility of the less desirable uses is a tradeoff for the opportunities opened up by the good ones. If CC is endorsing restrictions in this way we must be clear that our preference is a “commons first” approach.

This tension is not easily reconcilable. Instead, it suggests that preference signals are by themselves not sufficient to help sustain the commons, and should be explored as only a piece of a broader set of paths forward.

Existing Preference Signal Efforts

So far, this post has spoken about preference signals in the abstract, but it’s important to note that there are already many initiatives underway on this topic.

For instance, Spawning.ai has worked on tools to help artists find if their works are contained in the popular LAION-5B dataset, and decide whether or not they want to exclude them. They’ve also created an API that enables AI developers to interoperate with their lists; StabilityAI has already started accepting and incorporating these signals into the data they used to train their tools, respecting artists’ explicit opt-ins and opt-outs. Eligible datasets hosted on the popular site Hugging Face also now show a data report powered by Spawning’s API, informing model trainers what data has been opted out and how to remove it. For web publishers, they’ve also been working on a generator for “ai.txt” files that signals restrictions or permissions for the use of a site’s content for commercial AI training, similar to robots.txt.

There are many other efforts exploring similar ideas. For instance, a group of publishers within the World Wide Web Consortium (W3C) is working on a standard by which websites can express their preferences with respect to text and data mining. The EU’s copyright law expressly allows people to opt-out from text and data mining through machine-readable formats, and the idea is that the standard would fulfill that purpose. Adobe has created a “Do Not Train” metadata tag for works generated with some of its tools, Google has announced work to build an approach similar to robots.txt, and OpenAI has provided a means for sites to exclude themselves from crawling for future versions of GPT.

Challenges and Questions in Implementing Preference Signals

These efforts are still in relatively early stages, and they raise a number of challenges and questions. To name just a few:

• Ease-of-Use and Adoption: For preference signals to be effective, they must be easy for content creators and follow-on users to make use of. How can solutions be ease-to-use, scalable, and accommodate different types of works, uses, and users?
• Authenticating Choices: How best to validate and trust that a signal has been put in place by the appropriate party? Relatedly, who should be able to set the preferences — the rightsholder for the work, the artist who originally created it, both?
• Granular Choices for Artists: So far, most efforts have been focused on enabling people to opt-out of use for AI training. But as we note above, people have a wide variety of preferences, and preference signals should also be a way for people to signal that they are OK with their works being used, too. How might signals strike the right balance, enabling people to express granular preferences, but without becoming too cumbersome
• Tailoring and Flexibility Based on Types of Works and Users: We’ve focused in this post on artists, but there are of course a wide variety of types of creators and works. How can preference signals accommodate scientific research, for instance? In the context of indexing websites, commercial search engines generally follow the robots.txt protocol, although institutions like archivists and cultural heritage organizations may still crawl to fulfill their public interest missions. How might we facilitate similar sorts of norms around AI?

As efforts to build preference signals continue, we will continue to explore these and other questions in hopes of informing useful paths forward. Moreover, we will also continue to explore other mechanisms necessary to help support sharing and the commons. CC is committed to more deeply engaging in this subject, including at our Summit in October, whose theme is “AI and the Commons.”

Register for the CC Global Summit >

If you are in  New York City on 13 September 2023, join our symposium on Generative AI & the Creativity Cycle, which focuses on the intersection of generative artificial intelligence, cultural heritage, and contemporary creativity. If you miss the live gathering, look for the recorded sessions.

The post Exploring Preference Signals for AI Training appeared first on Creative Commons.

“The key to enjoying the benefits of Open Culture is to use the tools available to us” says Rina Pantalony. In this episode we learn about the national and global networks that support open access in the GLAM sector and how education is crucial to leveraging the power of open licenses. Copyright is a tool open licensing with attribution can accelerate the spread of information and knowledge.

Open Culture VOICES is a series of short videos that highlight the benefits and barriers of open culture as well as inspiration and advice on the subject of opening up cultural heritage. Rina Pantalony is the Dirctor of Copyright Services at Columbia University and is also on the advisory board of OCEAN, the Open Copyright Education Advisory Netowrk which advocates for open licensing around the world.

Rina responds to the following questions:

1. What are the main benefits of open GLAM?
2. What are the barriers?
3. Could you share something someone else told you that opened up your eyes and mind about open GLAM?
4. Do you have a personal message to those hesitating to open up collections?

Closed captions are available for this video, you can turn them on by clicking the CC icon at the bottom of the video. A red line will appear under the icon when closed captions have been enabled. Closed captions may be affected by Internet connectivity — if you experience a lag, we recommend watching the videos directly on YouTube.

Want to hear more insights from Open Culture experts from around the world? Watch more episodes of Open Culture VOICES here >>

The post Rina Pantalony — Open Culture VOICES, Season 2 Episode 22 appeared first on Creative Commons.

Crossposted with permission from The Michelson 20MM Foundation 23 Aug 2023 blog post.

Creative Commons licenses enable much of the open content across the arts, sciences, and academia, including open educational resources (OER). Creative Commons (CC) offers CC Certificate courses, or training on CC licensing and open tools, which have become a key tool for open communities around the world. Currently, 1,459 people from 65 countries have been  Creative Commons (CC) Certified, having taken and passed one of the CC Certificate courses. Given Governor Gavin Newsom’s historic investment in California Community Colleges’ (CCCs) Zero-Textbook-Cost (ZTC) degree programs, it is critical to ensure faculty, students, and staff have the capacity they need to create, use, and share the open resources supported by this funding. For this reason, The Michelson 20MM Foundation is elated to award a 2023 OER Spark Grant to Creative Commons.

“Creative Commons likes to say we put the open in open educational resources,” Jennryn Wetzler, Creative Commons Director of Learning and Training shared. “We have six different licenses and two public domain tools that enable creators to legally share their copyrighted content much more flexibly than traditional, ‘all rights reserved’ copyright. They’re applied to over 2.5 billion works online and enable sharing, enable adaptation, and remix — and so much innovation and learning.”

The Creative Commons Bootcamp is a proven model in California and beyond. CC has found that just one CC graduate on a campus can have a ripple effect — increasing open education awareness, acceptance, and use within their community. In January, Creative Commons, in partnership with the CCC Academic Senate’s OER Initiative, helped 12 individuals from the CCC system receive their CC Certification through a Michelson Spark Grant. Less than eight months later, the 12 graduates have hosted OER tutorials, planned OER conferences, developed LibreTexts training for faculty, and mapped ZTC conversions courses — further exemplifying the value of having a CC Certified individual on campus.

Building upon the success of the Bay Area Bootcamp, and acutely aware of the importance of an impactful ZTC funding implementation throughout the CCC system, CC is partnering with the CCC Academic Senate’s OER Initiative again to host a Bootcamp for 25 Southern California CCC faculty. Not only does the expanded training further the goal of bringing more CC Certified experts to the 116 CCCs, but also it provides key stakeholders within the CCC system the opportunity to be connected with OER and ZTC experts throughout the world, providing support as the newly CC Certified individuals work on creating, adopting, and maintaining ZTC programs on their campuses.

True to the nature of open access, CC Certificate courses are openly licensed, which enables graduates to not only reuse, but also remix the material within their institutions if other faculty and staff members are interested. This means that the investment in individuals from 25 community colleges has the potential to impact at least 22% of the CCC system.

As OER gains momentum throughout the state and nation, CC anticipates that the Bootcamp will fill up quickly. In order to ensure it has the intended impact, CC and the CCC Academic Senate will share registration information; they will focus on priority registration, but also establish a wait-list to maximize the number of CCC campuses involved. It will be exciting to see how the 25 campuses leverage the training and inspire other CCCs to embrace OER.

“OER lets students have access to the materials they need to succeed free of cost, largely due to open copyright and Creative Commons licenses,” Cailyn Nagle, OER Program Manager stated. “Creative Commons has been an invaluable resource to the state — and beyond — and we are thrilled to extend CC Bootcamp participation to an additional 25 California Community Colleges.”

Register now to earn a CC Certificate in 2023 or learn more about the CC Certificate Program.

The post How CC Will Advance Open Licensing Understanding Within 25 California Community Colleges appeared first on Creative Commons.

“Accessibility means putting art out there!” Sumona tells us in this episode about how Delhi’s Art Gallery (DAG) approaches open access from various perspectives. Sumona shares insight into creating exhibitions that inform the public and shed light on recent history in digital and physical spaces.

Open Culture VOICES is a series of short videos that highlight the benefits and barriers of open culture as well as inspiration and advice on the subject of opening up cultural heritage. Sumona is the Vice President of Museum Programs at DAG where she has worked with museum collections and the institutions own collection to increase access to cultural heritage.

Sumona responds to the following questions:

1. What are the main benefits of open GLAM?
2. What are the barriers?
3. Could you share something someone else told you that opened up your eyes and mind about open GLAM?
4. Do you have a personal message to those hesitating to open up collections?

Closed captions are available for this video, you can turn them on by clicking the CC icon at the bottom of the video. A red line will appear under the icon when closed captions have been enabled. Closed captions may be affected by Internet connectivity — if you experience a lag, we recommend watching the videos directly on YouTube.

Want to hear more insights from Open Culture experts from around the world? Watch more episodes of Open Culture VOICES here >>

The post Sumona Chakravarty — Open Culture VOICES, Season 2 Episode 21 appeared first on Creative Commons.

Many wonder what role CC licenses, and CC as an organization, can and should play in the future of generative AI. The legal and ethical uncertainty over using copyrighted inputs for training, the uncertainty over the legal status and best practices around works produced by generative AI, and the implications for this technology on the growth and sustainability of the open commons have led CC to examine these issues more closely. We want to address some common questions, while acknowledging that the answers may be complex or still unknown.

We use “artificial intelligence” and “AI” as shorthand terms for what we know is a complex field of technologies and practices, currently involving machine learning and large language models (LLMs). Using the abbreviation “AI” is handy, but not ideal, because we recognize that AI is not really “artificial” (in that AI is created and used by humans), nor “intelligent” (at least in the way we think of human intelligence).

CC licensing and training AI on copyrighted works

Can you use CC licenses to restrict how people use copyrighted works in AI training?

This is among the most common questions that we receive. While the answer depends on the exact circumstances, we want to clear up some misconceptions about how CC licenses function and what they do and do not cover.

You can use CC licenses to grant permission for reuse in any situation that requires permission under copyright. However, the licenses do not supersede existing limitations and exceptions; in other words, as a licensor, you cannot use the licenses to prohibit a use if it is otherwise permitted by limitations and exceptions to copyright.

This is directly relevant to AI, given that the use of copyrighted works to train AI may be protected under existing exceptions and limitations to copyright. For instance, we believe there are strong arguments that, in most cases, using copyrighted works to train generative AI models would be fair use in the United States, and such training can be protected by the text and data mining exception in the EU. However, whether these limitations apply may depend on the particular use case.

It’s also useful to look at this from the perspective of the licensee — the person who wants to use a given work. If a work is CC licensed, does that person need to follow the license in order to use the work in AI training? Not necessarily — it depends on the specific use.

• To the extent your AI training is covered by an exception or limitation to copyright, you need not rely on CC licenses for the use.
• To the extent you are relying on CC licenses to train AI, you will need to follow the relevant requirements under the licenses.

Another common question we hear is “Does complying with CC license conditions mean you’re always legally permitted to train AI on that CC-licensed work?”

Not necessarily — it is important to note here that CC licenses only give permission for rights granted by copyright. They do not address where other laws may restrict training AI, such as privacy laws, which are always a consideration where material contains personal data and are not addressed by copyright licensing. (Many kinds of personal data are not covered by copyright at all, but may still be covered by privacy-related regulations.)

For more explanation, see our flowchart regarding the CC licenses in this context, and read more in our FAQ on AI and CC licenses.

CC Licenses and outputs of Generative AI

In the current context of rapidly developing AI technologies and practices, governments scrambling to regulate AI, and courts hearing cases regarding the application of existing law, our intent is to give our community the best guidance available right now. If you create works using generative AI, you can still apply CC licenses to the work you create with the use of those tools and share your work in the ways that you wish. The CC license you choose will apply to the creative work that you contribute to the final product, even if the portion produced by the generative AI system itself may be uncopyrightable. We encourage the use of CC0 for those works that do not involve a significant degree of human creativity, to clarify the intellectual property status of the work and to ensure the public domain grows and thrives.

Beyond copyright

Though using CC licenses and legal tools for training data and works produced by generative AI may address some legal uncertainty, it does not solve all the ethical concerns raised, which go far beyond copyright — involving issues of privacy, consent, bias, economic impacts, and access to and control over technology, among other things. Neither copyright nor CC licenses can or should address all of the ways that AI might impact people. There are no easy solutions, but it is clear we need to step outside of copyright to work together on governance, regulatory frameworks, societal norms, and many other mechanisms to enable us to harness AI technologies and practices for good.

We must empower and engage creators

Generative AI presents an amazing opportunity to be a transformative tool that supports creators — both individuals and organizations — provides new avenues for creation, facilitates better sharing, enables more people to become creators, and benefits the commons of knowledge, information, and creativity for all.

But there are serious concerns, such as issues around author recognition and fair compensation for creators (and the labor market for artistic work in general), the potential flood of AI-generated works on the commons making it difficult to find relevant and trustworthy information, and the disempowering effect of the privatization and enclosure of AI services and outputs, to name a few.

For many creators, these and other issues may be a reason not to share their works at all under any terms, not just via CC licensing. CC wants AI to augment and support commons, not detract from it, and we want to see solutions to these concerns to avoid AI turning creators away from contributing to the commons altogether.

Join us

We believe that trustworthy, ethical generative AI should not be feared, but instead can be beneficial to artists, creators, publishers, and to the public more broadly. Our focuses going forward will be:

• To develop and share principles, best practices, guidance, and training for using generative AI to support the commons. We don’t have all the answers — or necessarily all the questions — and we will work collaboratively with our community to establish shared principles.
• To continue to engage our community and broaden it to lift up diverse, global voices and find ways to support different types of sharing and creativity.
• Additionally, it is imperative that we engage more with AI developers and services to increase their support for transparency and ethical, public-interest tools and practices. CC will be seeking to collaborate with partners who share our values and want to create solutions that support a thriving commons.

For over two decades we have stewarded the legal infrastructure that enables open sharing on the web. We now have an opportunity to reimagine sharing and creativity in this new age. It is time to build new infrastructure that supports better sharing with generative AI.

We invite you to join us in this work, as we continue to openly discuss, deliberate, and take action in this space. Follow along with our blog series on AI, subscribe to our newsletter, support our work, or join us at one of our upcoming events. We’re particularly excited to welcome our community back in-person to Mexico City in October for the CC Global Summit, where the theme is focused squarely on AI & the commons. Consider attending and being part of the conversation: Registration is open now.

The post Understanding CC Licenses and Generative AI appeared first on Creative Commons.

• What is Creative Commons?
• What is Open Culture?
• Where can you find CC licenses out in the world?
• How can you get involved in the CC Open Culture movement?

In the next episodes of the series we will be inviting panelists to speak about some other topics important to the Open Culture landscape including: Decolonization, Indigenization and Restitution; Open Culture & Artificial Intelligence; and Respectful Terminologies & Changing the Subject, and more.

Interested in getting more involved? Here are some ways you can stay up to date:

• Sign up for our newsletter, Open Culture Matters.
• Join the Open Culture Platform, where we provide a space to share resources, enhance collaboration and raise awareness on open access to digital cultural heritage, working with Galleries, Libraries, Archives and Museums (GLAMs) professionals and open advocates.
• Volunteer to help translate our resources into other languages.

We also welcome you to suggest other webinar topics you’d like to see — please reach out to culture@creativecommons.org with any ideas.

After two years of virtual summits, we are also excited to be hosting our first in person CC Summit in Mexico City from October 3–6. Please join us for more sessions on the intersections of Open Culture and topics like AI, traditional knowledge, and more.

The post Back to Basics: Open Culture for Beginners appeared first on Creative Commons.

CC is thrilled to be partnering with the Wikimedia Foundation to make Wikimania 2023 a reality. The gathering takes place 16–19 August both in Singapore and online. Whether you can make it to Singapore or not, register now to attend, participate, and access recorded sessions.

The CC and Wikimedian communities overlap in many ways and share common values and activities dedicated to building and sustaining open culture and knowledge. As a part of the program, CC team members are leading four sessions, outlined below. Many Wikimania attendees are also part of CC’s Global Network and platforms for copyright, open education, and open culture, or support CC in other ways. We celebrate this global gathering of people all working with shared values to realize common goals. Tune in to Wikimania with us!

Better Sharing in a World with AI: Creative Commons Looks Ahead

CEO Catherine Stihler and General Counsel Kat Walsh will kick off CC’s sessions with a joint keynote to guide participants through the journey CC has been on to understand how artificial intelligence (AI) intersects with CC’s 20-plus-year history of supporting open knowledge and culture globally with our licenses and legal tools. Then they will help participants look ahead to see how we can all advocate for policy and practices that ensure a world with AI will continue to support CC’s strategy of better sharing: sharing that is contextual, inclusive, just, equitable, reciprocal, and sustainable. Tune in: 2:00 UTC/10:00 SGT on Fri 18 Aug

Why Tackling Climate Change Needs Open Science and Open Culture

Open Climate Campaign Manager Monica Granados and Director of Policy and Open Culture Brigitte Vézina are leading a workshop about why tackling climate change needs both open science and culture. They describe: To arrive at solutions to climate change we need open access to knowledge. But climate change is caused by human activities, as such we also need open culture to understand why humans have caused climate change. In this workshop, we will remix public domain culture to raise climate awareness and highlight the need for both open climate and culture to solve climate change. Tune in: 3:15 UTC/11:15 SGT Fri 18 Aug

Building an Initiative for a Global Recommendation on Open Culture

CC’s open culture team will present how CC is building an initiative for a global recommendation on open culture. Team members Brigitte Vézina, Jocelyn Miyara, and Connor Benedict will report on what’s happening with the recommendation so far, including the May 2023 Lisbon meeting with global culture experts, and look to engage Wikimania’s broader and more diverse global participants in the initiative. Tune in: 6:55 UTC/14:55 SGT Fri 18 Aug

Exploring the Values That Will Shape AI for a Better internet

AI is deeply connected to networked digital technologies — from the bazillions of works harvested from the internet to train AI to all the ways AI is shaping our online experience, from generative content to recommendation algorithms and simultaneous translation. Representing the Movement for a Better Internet, co-founded by CC and other public-interest organizations, CC’s Director of Communications & Community Nate Angell is teaming up with consultant Shannon Hong to lead a workshop that will engage Wikimania participants directly in helping to shape how AI fits in to the Movement’s people-powered policy agenda. Tune in: 3:15 UTC/11:15 SGT Sat 19 Aug

The post CC at Wikimania 2023 appeared first on Creative Commons.

Are you thinking about how generative artificial intelligence (AI*) intersects with creativity? Or how it draws from existing works and collections? Or enables new understandings of culture?

Join Creative Commons in NYC on 13 September 2023 for a full-day symposium focused on the intersection of generative artificial intelligence, cultural heritage, and contemporary creativity.

Bringing together cultural heritage experts, contemporary creators working with AI tools, and platform builders: Our focus will be on the relationship between access and reuse of cultural heritage and contemporary creativity, and an exploration of AI tools as a new means of creative expression building on the commons.

Spots are limited! Register now to make sure you are part of the live conversation.

We are excited to share the program for a full-day public symposium on 13 September, featuring a series of panels tackling critical questions regarding the potential of AI tools for creators, cultural heritage institutions, and the general public. The proceedings will be recorded for online distribution after the event. We are grateful to our sponsors for their support of this event: Akin Gump LLP (lead symposium sponsor), Morrison Foerster LLP (workshop sponsor), and the Engelberg Center on Innovation Law & Policy at NYU Law School (hosting sponsor).

Meet our panelists: View or download the full program and schedule >

Can AI propel cultural heritage institutions through their digital transformation?

AI has been used as an enabler for several cultural heritage institutions’ (CHIs) transformational goals: from digitization, to preservation, to providing open access to users far and wide. How can digital and AI technologies help institutions realize their mission? This panel will probe the role of AI in ensuring CHIs’ relevance in the 21st century.

Can AI help everyone enjoy culture as a global public good?

In 2022, UNESCO declared culture a global public good, paving the way for culture to be recognized as a sustainable development goal in and of itself. The advent of AI technologies hold many promises to reduce the barriers for enjoyment of culture by people all over the world, especially for marginalized groups such as women, youth and Indigenous peoples. At the same time, AI may pose risks in perpetuating cultural power imbalances. This panel will strive to determine how AI can concretely support culture as a global public good.

Fair remuneration of creators — Can AI be an answer?

This panel will look at existing and potential remuneration models for creators in the age of AI and explore solutions for fair and equitable retribution of creators, including through the lens of distributive justice.

Copyright and open sharing of heritage collections and data: bounty or bane for creativity in the age of AI?

This panel will focus on some of the challenges posed by copyright, on a global scale, with regards to sharing of cultural heritage, with humans and machines. It will also explore the barriers that cultural heritage institutions face in sharing their collections, and the opportunities that emerge when they are able to do so.

Diversity, inclusivity, sustainability, and cultural identity — What role for AI?

This panel will focus on the necessary interplay between labeling of culture heritage materials and the creation of datasets for ML/AI, with a particular view to emerging practices around the ethical sharing of cultural heritage.

Creativity, machines and the heritage commons — What collaboration opportunities are there?

This panel will bring together those who are actively experimenting with and using AI technologies in conversation with creators and cultural heritage practitioners who steward heritage collections in the commons.

Users are creators — Is AI blurring the lines of creativity in the copyright framework?

With AI opening the doors to fresh modes of creative expression, the traditional roles of art creators and users blend into each other to offer new forms of collaborative creation. This panel will focus on the new intertwined patterns at play in the creativity process enabled by AI technologies.

Spots are limited! Register now to make sure you are part of the live conversation.

The post NYC Symposium: Generative AI & the Creativity Cycle appeared first on Creative Commons.

At CC we believe that to solve big problems, the knowledge and culture about those problems needs to be open and freely accessible. In line with our Open Climate Campaign, which focuses on opening up climate research, we recently launched the Open Climate Data project, to facilitate better sharing of climate data on a global scale. Making climate data more open and easily accessible is a crucial step towards addressing the climate crisis.

We started this project by asking a fundamental question: “What climate data exists, and what can I do with it?” To reach an answer, we conducted a landscape analysis to better understand the permissible uses of existing large climate data sets. We surveyed a range of organizations that provide climate data on behalf of national, intergovernmental and/or global populations and are both publishers and sources of climate data. This approach enabled us to assess the current status of major sources of climate data and propose practical ways in which it can be shared more effectively. We hope this initial analysis provides clarity to researchers, policymakers, educators, civil society organizations and advocates.

Read our Landscape Analysis report to learn more about how we analyzed large climate data sources, in accordance with the FAIR data principles: findability, accessibility, technical interoperability, and reusability (as dictated by licensing terms).

As the primary aim of the Open Climate Data project is to facilitate better sharing of climate data, we analyzed a range of data-sharing approaches from multiple sources including: US government, global NGOs, regional international governments, European governments, and global intergovernmental alliances.

Landscape Data Sources

US Government

• Atmospheric Radiation Measurement Data Center (ARM)
• Envirofacts
• Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE)
• National Centers for Environmental Information at NOAA
• NASA Earth Science Data Systems

Global NGOs

• GEOSS Portal
• International Energy Agency
• Sensor.Community
• The World Bank Group Climate Change Knowledge Portal
• WRI Data

Regional International Governments

• 3CN Climate Database: Latin America
• Asia-Pacific Data-Research Center (APDRC): Asia
• Chinese Academy of Science Earth: China
• IGAD Climate Predictions and Applications Centre: Africa

European Governments

• Atmosphere Data Store (ADS)
• CEDA Archive
• Climate Data Store
• European Space Agency Climate Change Initiative
• Met Office

Global Intergovernmental Alliances

• European Centre for Medium-Range Weather Forecasts (ECMWF)
• European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)
• The Food and Agriculture Organization of the U.N. Geographic Network
• International Renewable Energy Agency
• OECD Data
• UN Environment Programme Global Resource Information Database (GRID) – Geneva

FAIR Data Principles

Given the diverse range of climate data sponsors, publishers, and sources from around the world, we found a wide variety of methods for accessing climate data. Our goal was to understand how their climate data can be accessed in accordance with the FAIR data principles: findability, accessibility, technical interoperability, and reusability (as dictated by licensing terms). We examined how these climate data providers share their data today, and established a baseline of open climate data information by assessing each of these variables.

This project is dedicated to improving the sharing of climate data, and we place great importance on pursuing this goal collaboratively with the diverse range of stakeholders involved in addressing climate change. Our next step is to establish a dedicated working group of expert practitioners and representatives from regional and global climate data publishers and data source entities, and collectively, to develop a community sharing standard for open climate data. We hope to offer guidance to stewards of large open climate datasets and the broader climate data community — including those not involved in the original data creation — on best practices for sharing climate data in standardized ways that maximize accessibility, reuse and sharing.

We invite you to join us in our ongoing journey of learning and collaboration as we develop policies and practices to open up data for the advancement of climate research and innovation. Stay connected with us by emailing openclimatedata@creativecommons.org and subscribing to our newsletter.

The post Surveying the Open Climate Data Landscape appeared first on Creative Commons.

Watch A Special Episode of the Open Culture Voices Series, Part 1

In this Special Episode of the Open Culture Voices series, CC hosts a conversation among five open culture experts from around the world:

• Dr. Andrea Wallace, Professor, University of Exeter Law School, United Kingdom
• Dr. Nkem Osuigwe, Director, African Library and Information Associations and Institutions, Ghana
• Medhavi Gandhi, Founder, The Heritage Lab, India
• Evelin Heidel (Scann), Program Lead at Wikimedistas de Uruguay, Uruguay
• Michael Peter Edson, Founding Director, Museum of Solutions, USA/India

This second part of the conversation revolves around several topics related to open culture, such as digital interactions, the climate crisis, and the challenges faced by the open culture movement. Our guests discuss the potential of open knowledge and culture in addressing environmental concerns, promoting diversity and access, and influencing policy changes.

Some of the other key points discussed include:

• The material impact of digital technologies on the climate crisis and the need for more sustainable approaches to other societal challenges and the position that cultural institutions — like galleries, libraries, archives, and museums, or GLAMs — should not shy away from digital for fear of the digital footprint.
• The pivotal role of cultural institutions as actors of change to promote open culture — as well as the huge cultural participation culture outside institutions. The universal fundamental right to participate in cultural life can be very hard to enjoy — openness can be a tool to help people engage with culture.
• The importance of collaboration and organization across institutions to achieve common goals — sharing and comparing experiences can lead to institutional standards that can in turn influence policy in meaningful ways to advance open culture.
• The challenges and ethical considerations surrounding the participation of individual creators and artisans in open culture — it is also important to reflect on who open culture might be pushing away and whose livelihoods it might threaten.
• The importance of funding for institutions and the need to support open culture initiatives financially.
• The potential for working with platforms to incorporate licensing options and improve copyright awareness.
• The potential impact of open culture in shaping and influencing society during times of change, such as the climate crisis.

These points reflect our guests’ perspectives on the challenges and opportunities within the open culture movement and their suggestions for realizing its potential.

Here’s what our guests believe needs to change if we want to realize open culture:

“I think that cultural heritage institutions need to move away from a risk-based approach into a transformational one…They have a lot of leverage on changing the conversation around copyright and I think that they need to use it.” — Evelin Heidel (Scann)

“Making sure that we elect people who fund the public sector, fund institutions, set up funding schemes for artists, for creatives, for people to do research and really cool projects around some of these things.” — Andrea Wallace

“One could take the point of view that the toolkits are there, that there doesn’t need to be some massive intervention. It can be used, reapplied, remixed, to solve local problems, policy problems, execution problems at any scale… I still see this as a point of inflection. We’ve built two thirds of a bridge, and we’re curious why people haven’t crossed that bridge.” — Michael Peter Edson

“Support in funding, especially for institutions which do grapple with whether to open, whether it will take away from their monetization practices…It’s nice to have web monetization going and maybe support that” — Medhavi Gandhi

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Want to hear more insights from Open Culture experts from around the world? Watch more episodes of Open Culture VOICES here >>

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