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Final public hearings on Competition Amendment Bill

Publish date: 02 November 2018
Issue Number: 46
Diary: CompliNEWS
Category: Legislation

In anticipation of a final round of public hearings on the Competition Amendment Bill, the NCOP’s Economic and Business Development Committee has called for written submissions ‘B’ version adopted last week by the National Assembly, reports Pam Saxby for CompliNEWS. According to a memorandum on its objects, the Bill’s overarching purpose is to address ‘two persistent structural constraints on the South African economy’: ‘high levels of economic concentration’ and a ‘skewed ownership profile’. With that in mind, once in force among other things the proposed new statute will make it a prohibited practice for any dominant firm to avoid purchasing or refuse to purchase goods or services from a small or medium business controlled or owned by historically disadvantaged persons. Provisions on prohibiting price discrimination by dominant firms reflect similar intentions.

In addition, a committee will be established to determine whether ‘a merger involving a foreign acquiring firm’ is likely to have ‘an adverse effect on … (SA’s) national security interests’. According to Economic Development Minister Ebrahim Patel, the Bill is underpinned by ‘broad agreements’ on ‘key concepts’ reached in the National Economic Development and Labour Council by government and its social partners. ‘We’ve taken a major, potentially very controversial piece of legislation and secured, through social dialogue, a significant understanding of what we seek to do and an acceptance that we’ve struck an effective balance between all … the imperatives,’ Economic Development Minister Ebrahim Patel told members of the National Assembly committee concerned when they began deliberations on the Bill last month.

 

Working Smart

By Lee Rossini

Although still in its infancy, the term agentic AI is being heard more frequently. It refers to AI that can act autonomously to achieve goals, make decisions, and adapt to changing environments with minimal human intervention. Unlike traditional AI models that respond only to direct prompts, agentic AI systems are designed with a sense of 'agency': they can plan, execute multi-step tasks, interact with other systems, and learn from outcomes. These systems often combine reasoning, memory, and tool usage, enabling them to operate more like digital collaborators than passive tools.

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