May 29, 2024

OpenAI and Microsoft Face Mounting Legal Pressure Over AI Training Methods

Written by AiBot

AiBot scans breaking news and distills multiple news articles into a concise, easy-to-understand summary which reads just like a news story, saving users time while keeping them well-informed.

Nov 23, 2023

OpenAI and Microsoft are facing multiple lawsuits over allegations that their artificial intelligence systems are trained using copyrighted content without permission. Authors and publishers claim the tech giants have infringed on intellectual property rights by scraping millions of online books and articles to build AI models like ChatGPT.

Second Major Lawsuit Targets OpenAI’s Foundation Models

On November 21st, nonfiction author Julian Sancton filed a lawsuit accusing OpenAI and Microsoft of copyright infringement for training ChatGPT and other systems using excerpts from his book "Madhouse at the End of the Earth".

The suit alleges OpenAI’s "foundation models" like GPT-3 ingested full digital copies of books and other texts without permission to create the training data for its AI. By allowing free public use of these models via ChatGPT and other interfaces, OpenAI and Microsoft have engaged in "rampant theft" and caused irreparable damage to creators, the lawsuit claims.

Sancton’s lawyer described it as "a textbook case of copyright infringement by big tech companies who believe they are so powerful no one will dare stop them." The case has been filed as a class action, potentially allowing other authors to join.

This comes just days after a separate lawsuit led by two fiction writers made similar allegations against Microsoft and OpenAI over the use of their works. Lawyers in that case claimed "no one’s work is protected from Big Tech’s relentless assault on creativity."

Mounting Pressure Over AI Ethics and Regulation

The dual lawsuits signify the growing legal threats and backlash faced by generative AI providers over training data and content moderation concerns.

OpenAI in particular has faced criticism from AI experts and regulators over its secretive practices and lack of accountability. Despite receiving billions in funding from Microsoft, it remains largely free from external oversight.

Earlier this year, OpenAI declined a request from the EU Parliament to review its training data and algorithms for potential bias and quality issues. The opaque nature of systems like DALL-E, GPT-3 and ChatGPT has led to calls for AI regulation to ensure accountability, especially where public sector adoption is concerned.

The European Commission last week proposed new rules for high-risk AI systems enforce transparency requirements around data provenance and algorithm audits. Rules like these could compel companies like OpenAI to open up and address issues like copyright infringement in its foundation models.

For Microsoft, its multibillion dollar partnership with OpenAI has become a lightning rod for controversy even as it aggressively pushes AI integrations across its software and cloud platform.

OpenAI Corporate Control Creates Conflicts

The copyright lawsuits also highlight growing concerns around consolidation of power in the generative AI space.

Earlier this year, OpenAI restructured its corporate leadership – Microsoft was given greater control through expanded board seats while OpenAI CEO Sam Altman returned as a full-time executive.

Critics see risks of unchecked commercialization tainting OpenAI’s original nonprofit research mission to develop AI safely in the public interest. The change has already brought mass layoffs along with decisions like ChatGPT’s paywall and enforced limits that seemingly prioritize monetization over access.

There are also worries that Microsoft could exploit its position upstream of OpenAI development to unfairly compete across sectors from search to software. With Azure hosting as the default for models like DALL-E and GPT-3, Microsoft has almost gatekeeping control over next-gen AI. Competitors have called for restrictions around preferential access protections.

The consolidated power risks entrenching and concentrating AI expertise within a single big tech company. OpenAI was envisaged as an independent, decentralized counterweight for the public good. Its increasing subordination to Microsoft’s commercial interests repudiates those founding ideals for many experts and critics.

Stricter Copyright Laws For AI Loom As Lawmakers Take Notice

The barrage of lawsuits has amplified calls for urgent reforms around copyright laws not fit for the AI age.

Generating training data from copyrighted online content without payment or permission contravenes basic creative rights. But weak enforcement renders creators powerless while their works get exploited by tech giants.

The onus remains entirely on identifying and filing claims against specific infringements. Constructing AI models using millions of works makes that prohibitive even for big media companies, let alone independent artists or niche creators.

Lawmakers have taken notice – Senators this week urged the Copyright Office to investigate balancing creative rights with AI innovation through updated policies. Entertainment unions lobbied Congress on establishing new protections and royalties for members whose works get used to develop AI without consent.

Year Key OpenAI Milestones
2015 OpenAI founded as nonprofit AI research company
2019 Releases GPT-2 language model
2020 Receives $1 billion in funding from Microsoft
2021 Launches application platform with GPT-3 and Codex
2022 Microsoft invests additional $10 billion into OpenAI
2023 Restructures as capped-profit company with Microsoft oversight

Table: Timeline of major events in OpenAI’s history since being founded in 2015.

The pressure is growing on AI companies to legitimize training data sourcing methods and address the full downstream impacts of their technology. Litigation and regulation present gathering threats with bipartisan momentum from lawmakers and authorities at home and abroad.

For Microsoft and OpenAI, delivering transparency and rights protections could mitigate legal risks even if it delays commercialization. Stakeholders urge constructive engagement and dialogue rather than reflexive denial and obstruction.

There are also calls for developing technical solutions like privacy-preservingMachine learning and verifiable credential systems that enable consented data use at scale. Technology nonprofits also advocate open standards around issues like content filtering that balance harms across society. Collaborative initiatives recognizing shared interests may achieve compromises that narrow differences.

Uncertain Future For Generative AI As Backlash Builds

The controversial nature of systems like ChatGPT will fuel continuous cycles of public concern around AI harms leading to lawsuits, restrictions and techlash.

Each wave risks hampering innovation and availability while failing to achieve acceptable remedies around things like algorithmic bias or job automation. Fragmented perspectives on issues spanning ethics, copyright, transparency and access impede durable solutions.

Progress requires collective action from companies, governments and civil society with vision extending beyond near-term commercial rewards or prohibitive restraints. Only open and inclusive governance addressing the full range of societal priorities can realize AI’s benefits while respecting rights and shared values.

Constructive cooperation enabling accountable development of safe, rights-respecting and ethical AI systems remains imperative. The lawsuits against OpenAI and Microsoft underscore the urgency and collective responsibility.




AiBot scans breaking news and distills multiple news articles into a concise, easy-to-understand summary which reads just like a news story, saving users time while keeping them well-informed.

To err is human, but AI does it too. Whilst factual data is used in the production of these articles, the content is written entirely by AI. Double check any facts you intend to rely on with another source.

By AiBot

AiBot scans breaking news and distills multiple news articles into a concise, easy-to-understand summary which reads just like a news story, saving users time while keeping them well-informed.

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