FairCVreview: A novel platform to advance trust in the compliance and fairness of AI systems for the recruitment sector by providing fully transparent and bias-free AI systems.

FairCVreview是一个基于人工智能的简历筛选工具，注重公平性和透明度。它基于一个易于使用的界面，即使是最小的招聘公司也可以使用最新的技术，而不需要编码或技术技能来操作。筛选技术侧重于公平性，使用人工智能来识别和消除基础数据中的偏见。输出充分解释，使招聘人员，求职者和雇主都可以充分信任的公平选择。招聘人员和雇主将看到决策过程的细节，并获得平等参数的指标。他们将能够与申请人分享细节，解释他们没有被选中的原因（例如，表明与被选中的候选人相比，他们缺乏哪些技能或资格）。提供了多样性指标，以便雇主能够发现任何问题并采取措施解决这些问题。例如，如果候选人缺乏多样性，那么雇主可以改进他们的广告策略，以鼓励更广泛的申请人。此外，求职者将能够通过我们额外的面向公众的应用程序测试他们自己的简历。这将提供一个用户友好的界面，允许个人上传他们的简历，它将标记任何可能使他们受到偏见的元素。例如，如果他们包含了透露年龄的细节，他们会被提示考虑是否有必要这样做。FairCVreview将采用与客户代表（招聘人员）合作的方式进行开发。首先，我们将确定可能影响项目的偏见类型，我们将确定可能受到影响的目标群体和关键维度（例如性别、种族、年龄等）。这包括与学科专家合作，识别存在于底层数据中的偏见，以及机器学习处理过程中可能出现的偏见。在人工智能开发和培训期间，我们将评估所有潜在维度的偏差输出，并根据绩效指标对其进行评分，从而使我们能够识别和减轻任何偏差。其次，我们将提供透明的结果，向招聘人员/雇主反馈简历达到匹配分数的确切原因。为了实现这一目标，我们将利用我们在论文阅分领域开发类似可解释性技术的经验（该领域使用类似的方法来消除偏见并提供透明的结果）。

FairCVreview is an AI-based CV screening tool that focuses on fairness and transparency. It is based on an easy-to-use interface that gives even the smallest recruitment companies access to the latest technologies without needing coding or technical skills to operate.The screening technology focuses on fairness, using AI to identify and eliminate the bias in underlying data. The outputs are fully explained so that recruiters, job applicants and employers can all have full confidence in the fairness of the selection.Recruiters and employers will see details of the decision-making process and get metrics on equality parameters. They will be able to share details with applicants to explain why they have not been selected (e.g. indicating which skills or qualifications were lacking compared to the selected candidates).Diversity metrics are provided so employers can identify any issues and take steps to address them. For example, if the candidate pool lacks diversity then the employer could improve their advertising strategies to encourage a broader range of applicants.Additionally, Job seekers will be able to test their own CV via our additional public-facing application. This will provide a user-friendly interface allowing individuals to upload their CV and it will flag any elements that could potentially expose them to bias. For example, if they have included details that give away their age, they will be prompted to consider if this is necessary.FairCVreview will be developed using a collaborative approach with input from customer representatives (recruiters).Firstly, we will identify the types of bias that could potentially impact the project and we will identify the target groups and key dimensions that could be impacted (e.g. gender, ethnicity, age, etc).This includes working with subject experts to identify bias that exists in the underlying data as well as any that can arise during machine learning processing. During AI development and training, we will evaluate the outputs for bias across all potential dimensions and these will be scored against performance metrics, allowing us to identify and mitigate against any bias.Secondly, we will deliver transparent results, giving feedback to the recruiter/employer on exactly why the CV achieved that match score. To achieve this, we will build on our experience in developing similar explainability technology for the essay marking sector (which uses a similar approach to eliminate bias and deliver transparent results).