Newsroom Anthropic 09月13日
AI工具在选举中的使用与监管
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2024年美国选举成为首个广泛使用生成式AI工具的选举周期。自2023年7月以来,我们已采取措施检测和减轻工具的潜在滥用,并引导用户访问权威选举信息。在2024年11月5日的美国联邦、州和地方选举前,我们分享了迄今为止的工作总结。我们更新了使用政策,禁止使用我们的产品进行政治竞选和游说,禁止生成关于选举法律、候选人和其他相关主题的错误信息,并限制Claude只能生成文本,以消除选举相关深度伪造的风险。我们还开发了改进的工具来检测协调行为或其他选举相关滥用行为,并与AWS和Google Cloud Platform合作,检测和减轻在这些平台上访问Anthropic模型的选举相关危害。我们定期进行红队演练和漏洞测试,以评估我们的系统对选举问题相关提示的响应,并防止大规模的错误信息。我们还不断改进我们的控制措施,以应对已识别的风险。

🔍 我们更新了使用政策,禁止使用我们的产品进行政治竞选和游说,禁止生成关于选举法律、候选人和其他相关主题的错误信息,并限制Claude只能生成文本,以消除选举相关深度伪造的风险。

🛡️ 我们开发了改进的工具来检测协调行为或其他选举相关滥用行为,包括严格执法、利用claude.ai上的提示修改、审计我们第一方API上的用例、在极端情况下暂停账户,并与AWS和Google Cloud Platform合作。

📊 我们定期进行红队演练和漏洞测试,以评估我们的系统对选举问题相关提示的响应,并防止大规模的错误信息。我们不断改进我们的控制措施,以应对已识别的风险。

📌 我们将用户重定向到可靠的投票信息,例如TurboVote,并分享我们的学习成果,以帮助其他人改进他们自己的选举诚信工作。

🗳️ 我们与全球政策制定者、民间社会组织和其他行业人士会面,讨论我们的选举工作并为我们的工作提供信息。我们还进行了主动的场景规划,以更好地准备美国选举日前潜在的选举相关滥用行为。

2024 marks the first United States (U.S.) election cycle where generative AI tools are widely available. Since July 2023, we have taken concrete steps to help detect and mitigate against the potential misuse of our tools and to direct users to authoritative election information. Ahead of federal, state, and local elections in the U.S. on November 5, 2024, we are sharing a summary of our work thus far.

Our policy approach

In May, we updated our Usage Policy to provide clarity around prohibited uses when it comes to elections and voting:

    Prohibit campaigning & lobbying: We prohibit the use of our products for political campaigning and lobbying. Under our policy, Claude cannot be used to promote a specific candidate, party or issue; for targeted political campaigns; or for soliciting votes or financial contributions.Combating misinformation & election interference: We prohibit the use of our products to generate misinformation on election laws, candidates, and other related topics. We also do not allow Claude to be used to target voting machines or obstruct the counting or certification of votes.Limiting outputs to text only: Claude cannot generate images, audio or videos, eliminating the risk of election related deepfakes.

We have also developed improved tools for detecting coordinated behavior or other elections-related misuse of our systems:

    Strict enforcement: To detect and prevent misuse, we deploy automated systems to enforce our policies and audit those systems with human review. We use a variety of methods to mitigate misuse, including:
      Leveraging prompt modifications on claude.aiAuditing use cases on our first-party APIIn some extreme cases, suspending accountsWorking closely with Amazon Web Services (AWS) and Google Cloud Platform (GCP) to detect and mitigate election-related harms from users accessing Anthropic models on those platforms.

Evaluating and refining our interventions

We regularly conduct targeted red-teaming to examine how our systems respond to prompts related to election issues.

    Ongoing vulnerability testing: We use in-depth testing conducted in collaboration with external subject matter experts, called Policy Vulnerability Testing (PVT), to identify potential risks. We focus on misinformation, bias and adversarial abuse by identifying relevant questions (e.g., asking where and how someone can vote in the US election), document model responses, and note the presence of “safety interventions,” like declining to answer harmful questions.Preventing misinformation at scale: We have built automated evaluations to test our systems at scale for a variety of election-related risks and assess the effectiveness of our interventions. These include ways of testing for:
      Political parity in model responses across candidates and topicsThe degree to which our systems refuse to respond to harmful queries about the electionHow robust our systems are in preventing misinformation and voter profiling tactics
    Improving our controls: In response to the findings, we continuously adapt our policies, strengthen our enforcement processes, and make technical refinements to the models themselves to address identified risks and make our systems more robust.

Providing accurate information and ensuring transparency

Because our models are not trained frequently enough to provide real-time information about elections, we redirect users to accurate, up-to-date and authoritative voting information for elections-related queries.

    Redirecting to reliable voting information: We implemented a pop-up giving users the option to be redirected to TurboVote (a nonpartisan resource from Democracy Works) if they ask for voting information.
      Recently, Turbovote was updated to include the names of all candidates running in federal and state elections, as well as ballot propositions.
    Referencing the model’s “knowledge cut off date:” We have also updated Claude’s system prompt to include a clear reference to its knowledge cutoff date (the date up to which Claude’s training data extends).Sharing learnings: To help others improve their own election integrity efforts and drive better safety outcomes across the industry, we released some of the automated evaluations we developed and launched an initiative to fund third-party evaluations that effectively measure AI capabilities and risks.

Throughout this year, we’ve met with global policymakers, civil society organizations, and others in industry to discuss our election work and inform our efforts. We’ve also engaged in proactive scenario planning to better prepare for potential election related abuse in the lead-up to election day in the U.S.

We cannot anticipate every way people might use our models related to elections, but we have and will continue to learn from and iterate on our processes, testing and improving our systems along the way.

Additional resources:

Relevant safety work: 

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相关标签

AI工具 选举 监管 错误信息 投票信息
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