JANZZ.technology’s Seven Principles for AI Ethics in HR Tech

Since the company’s founding in 2008, our mission has been to improve lives by creating software that promotes equal employment opportunities for everyone. We are committed to ethical and responsible use of technologies and data, developing software systems based on explainable AI that are safe, transparent, unbiased, and thus beneficial to individuals, organizations and communities. To ensure this, we have developed seven core ethics principles for AI in HR tech that we diligently follow—not only across the AI lifecycle, but across our entire organization. After all, AI ethics cannot exist in a vacuum. They can only emerge from a comprehensive ethical approach of the organizations building and deploying AI technologies. Ethical, by design.

humans

We design our technologies to help humans, not to replace them. We view AI as a tool to help humans make better decisions in less time and to unite the best talent with the best jobs – regardless of age, gender, ethnicity or any other characteristics not related to job performance. To help businesses and communities thrive, strengthening economies and building a better future.

bias

Our systems consistently separate personal data and job-related information. Our technologies use only anonymized, job-relevant data in the matching processes as well as hand-selected and carefully calibrated gold-standard training data for our machine learning models. This ensures completely unbiased results in parsing, matching, classification and analytics. To support candidate selection and talent or labor market management processes that are fair, transparent and non-discriminatory.

diversity

We support organizations in following best practices for fairness and inclusion. Achieving measurably fair and inclusive hiring outcomes and labor market integration requires both biasfree matching technology and reliable demographic data for diversity analytics. We provide both through our approach of separating candidate/employee information into anonymized, job-related data and personal data that includes key demographic data such as gender, age, race, and ethnicity.

transparency

Our solutions are based on fully explainable AI and human-in-the-loop models. The datasets and knowledge representations at the heart of our technologies are carefully curated, annotated and validated by humans. This ensures that all results and intermediate steps make rational sense, and that rankings and analytics are not based on spurious machine-made relationships. For example, our matching solutions provide clear explanations on how well and why candidates match jobs. This feedback can also help unsuitable candidates increase their career self-awareness.

privacy

Our technologies and solutions are fully compliant with all GDPR/CCPA and ISO 27001 requirements as well as all other data privacy and security regulations of the respective markets and countries we operate in. Using AI technology to process sensitive personal data involves a high degree of risk to the rights and freedoms of individuals. We take great care in designing solutions and systems that protect these rights and freedoms, ensuring users are always in control of their data.

accountability

We consistently foster accountability in our AI systems throughout their lifecycle, training them with hand-selected gold standard data, supervising each critical step and ensuring the systems function as intended. Accountability means that not only can the AI system explain its decisions, the developers and users of the system can also explain its decisions, their own decisions, and have a clear understanding of who is accountable for which decisions and to whom. To support this, we proactively educate ourselves, our customers and our users on the capabilities, potential and limitations of our solutions.

trust

We take an active role in developing trust in our AI technologies with our customers and users through a multifaceted approach. We adhere to and advocate our own ethical principles, the OECD’s principles on AI, and the strictest regulations concerning data privacy and data security. We offer our customers in-depth training and expert support in change management. We also encourage critical thinking and provide free educational content to increase transparency and awareness around how AI is used in HR tech, and the risks and opportunities it brings. So that everyone has the facts.

JANZZ.technology’s Seven Principles for AI Ethics in HR Tech

1

Benefit

humans

2

Reduce

bias

3

Support

diversity

4

Improve

transparency

5

Respect

privacy

6

Establish

accountability

7

Foster

trust

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