加拿大两大行业协会ACSESS和NACCB宣布合并加拿大咨询企业国家协会(NACCB)和加拿大猎头、就业和人员服务协会(ACSESS)决定合并,计划在2025年1月1日正式生效。此次合并旨在通过一个统一的组织更好地代表加拿大的人员配置行业,为成员提供法规更新、合规教育和操作工具等支持。NACCB主席Michael Leacy指出,未来独立承包商仍是协会关注的重点之一,而ACSESS则继续在立法变动和监管更新上提供指导。两大协会的领导者一致认为,这一联盟将更好地服务于IT、工程、金融和法律等专业人才配置领域的企业需求,加强行业在政策制定中的影响力。、
加拿大两大行业协会ACSESS和NACCB宣布合并
加拿大咨询企业国家协会(National Association of Canadian Consulting Businesses,NACCB)将与加拿大猎头、就业和人员服务协会(Association for Canadian Search, Employment and Staffing Services,ACSESS)合并。
计划是通过该联合组织,以一个统一的声音来代表加拿大的人员配置行业。
NACCB代表着专业配置公司和咨询行业。这一合并决定承认了人员配置行业的发展,因为该行业的发展使得NACCB和ACSESS的业务定位越来越接近,根据宣布合并的信函所述。随着这一发展,这两个组织在使命和战略目标上也逐步趋同。
“NACCB一直专注于包括IT、工程、金融和法律在内的专业配置,”NACCB的主席Michael Leacy在宣布合并的信中表示。“在合并后的协会中,独立承包商的角色仍将是一个重要的关注和支持领域。”
Leacy继续说道:“我们的会员将受益于ACSESS在全国立法和监管变化方面提供的指导,并能够接收到相关建议。通过加入这个统一的协会,他们还将获得合规教育以及各种运营工具。”
在今年早些时候,在Leacy和ACSESS主席Darlene Minatel的指导下,双方进行了有条不紊的协商。两个组织一致通过了合并决议,该合并将于2025年1月1日生效。
“每个组织的领导层都认识到,扩大后的协会在全加拿大范围内的代表性将有助于保持专业配置公司和咨询行业在政策决策中的重要利益,”该合并声明中提到。
Workday: It’s Time to Close the AI Trust GapWorkday, a leading provider of enterprise cloud applications for finance and human resources, has pressed a global study recently recognizing the importance of addressing the AI trust gap. They believe that trust is a critical factor when it comes to implementing artificial intelligence (AI) systems, especially in areas such as workforce management and human resources.
Research results are as follows:
At the leadership level, only 62% welcome AI, and only 62% are confident their organization will ensure AI is implemented in a responsible and trustworthy way. At the employee level, these figures drop even lower to 52% and 55%, respectively.
70% of leaders say AI should be developed in a way that easily allows for human review and intervention. Yet 42% of employees believe their company does not have a clear understanding of which systems should be fully automated and which require human intervention.
1 in 4 employees (23%) are not confident that their organization will put employee interests above its own when implementing AI. (compared to 21% of leaders)
1 in 4 employees (23%) are not confident that their organization will prioritize innovating with care for people over innovating with speed. (compared to 17% of leaders)
1 in 4 employees (23%) are not confident that their organization will ensure AI is implemented in a responsible and trustworthy way. (compared to 17% of leaders)
“We know how these technologies can benefit economic opportunities for people—that’s our business. But people won’t use technologies they don’t trust. Skills are the way forward, and not only skills, but skills backed by a thoughtful, ethical, responsible implementation of AI that has regulatory safeguards that help facilitate trust.” said Chandler C. Morse, VP, Public Policy, Workday.
Workday’s study focuses on various key areas:
Section 1: Perspectives align on AI’s potential and responsible use.
“At the outset of our research, we hypothesized that there would be a general alignment between business leaders and employees regarding their overall enthusiasm for AI. Encouragingly, this has proven true: leaders and employees are aligned in several areas, including AI’s potential for business transformation, as well as efforts to reduce risk and ensure trustworthy AI.”
Both leaders and employees believe in and hope for a transformation scenario* with AI.
Both groups agree AI implementation should prioritize human control.
Both groups cite regulation and frameworks as most important for trustworthy AI.
Section 2: When it comes to the development of AI, the trust gap between leaders and employees diverges even more.
“While most leaders and employees agree on the value of AI and the need for its careful implementation, the existing trust gap becomes even more pronounced when it comes to developing AI in a way that facilitates human review and intervention.”
Employees aren’t confident their company takes a people-first approach.
At all levels, there’s the worry that human welfare isn’t a leadership priority.
Section 3: Data on AI governance and use is not readily visible to employees.
“While employees are calling for regulation and ethical frameworks to ensure that AI is trustworthy, there is a lack of awareness across all levels of the workforce when it comes to collaborating on AI regulation and sharing responsible AI guidelines.”
Closing remarks: How Workday is closing the AI trust gap.
Transparency: Workday can prioritize transparency in their AI systems. Providing clear explanations of how AI algorithms make decisions can help build trust among users. By revealing the factors, data, and processes that contribute to AI-driven outcomes, Workday can ensure transparency in their AI applications.
Explainability: Workday can work towards making their AI systems more explainable. This means enabling users to understand the reasoning behind AI-generated recommendations or decisions. Employing techniques like interpretable machine learning can help users comprehend the logic and factors influencing the AI-driven outcomes.
Ethical considerations: Working on ethical frameworks and guidelines for AI use can play a crucial role in closing the trust gap. Workday can ensure that their AI systems align with ethical principles, such as fairness, accountability, and avoiding bias. This might involve rigorous testing, auditing, and ongoing monitoring of AI models to detect and mitigate any potential biases or unintended consequences.
User feedback and collaboration: Engaging with users and seeking their feedback can be key to building trust. Workday can involve their customers and end-users in the AI development process, gathering insights and acting on user concerns. Collaboration and open communication will help Workday enhance their AI systems based on real-world feedback and user needs.
Data privacy and security: Ensuring robust data privacy and security measures is vital for instilling trust in AI systems. Workday can prioritize data protection and encryption, complying with industry standards and regulations. By demonstrating strong data privacy practices, they can alleviate concerns associated with AI-driven data processing.
SOURCE Workday