Full Report
In early 2002 i suggested that we could solve some computer problems and south africas street-kid problem by setting up a network of street=kids with basic education to handle tasks computers still struggled with. At the time we were concerned with low-false positive, agentless remote detection of defaced web-sites, but also ran into the idea when we first built e-or, our early web application scanner. I suspect i didnt broach the subject with enough sensitivity (and in retrospect suggesting that remote controls for automatic gates could be replaced by 2 low cost street-kids (one as a spare)) might not have helped my cause..
Analysis Summary
# Main Topic
Historical concept proposed in early 2002 regarding utilizing educated individuals (initially framed contextually as "street-kids") in South Africa to handle complex computational tasks that automated tools struggled with—contrasted later with Amazon Mechanical Turk (MTURK).
## Key Points
- The initial proposal focused on solving computer problems and addressing socio-economic issues by establishing a network of educated individuals to perform complex tasks inaccessible to computers at the time.
- The context for the initial idea included developing low-false positive, agentless remote detection capabilities for defaced websites.
- The concept also arose during the development of "e-or," an early web application scanner.
- A notable, highly insensitive example cited was suggesting human intervention to replace remote controls for automatic gates.
- The author reflects that the modern concept validates this approach, citing Amazon MTURK as a service that solves difficult computer problems using human intelligence.
## Threat Actors
- No specific malicious threat actors or cybercriminal groups are mentioned in relation to the initial concept or the subsequent validation via MTURK.
## TTPs
- The primary technical goal implied by the initial concept was: **Low-False Positive, Agentless Remote Detection of Defaced Web-sites.**
- The "human intelligence" method (analogous to MTURK) functions as a solution for tasks where algorithms fail (e.g., captchas, complex visual analysis).
## Affected Systems
- **Targeted Systems/Tasks (Initial Intent):** Web-sites requiring defacement detection.
- **Related Tool Mentioned:** "e-or," an early web application scanner.
- **Broader Application:** Any task difficult for current algorithms (e.g., CAPTCHA solving, visual object recognition).
## Mitigations
- **Implied Mitigation/Solution (Historical):** Employing human intelligence networks for tasks computers cannot reliably automate, specifically for improved accuracy in security detection (low false positives).
- **Modern Context:** Utilizing services like Amazon MTURK to outsource difficult classification or analysis tasks.
## Conclusion
The core intelligence here is retrospective validation of a conceptual approach: using human cognitive ability to overcome technological limitations in automated processes, specifically noted in the security context of complex web monitoring. While the initial framing was poorly executed, the underlying principle aligns with modern crowdsourcing efforts used to solve nuanced detection problems.
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# Morning News Roll-up {Current Date Placeholder - September 12, 2007 Context}
## Overview
This compilation reflects historical concepts related to leveraging human intelligence for computationally difficult tasks, drawing a parallel between an early 2002 internal proposal and the subsequent emergence of Amazon Mechanical Turk (MTURK) for similar purposes.
## Top Stories
### The Precursor to Outsourced AI: Early 2002 Proposal for Human Computing Networks
- Summary: An early concept floated in 2002 suggested solving technical challenges (like accurate web defacement detection) and societal issues by creating a network of educated local individuals to handle tasks beyond computer capabilities.
- Source: Context derived from the main article narrative.
### Amazon Mechanical Turk (MTURK) Validates Human-in-the-Loop Model
- Summary: The emergence of MTURK confirms the utility of enlisting human workers for tasks difficult for automation, such as CAPTCHA solving, validating the author's prior, albeit poorly framed, suggestion.
- Source: Derived from the comparison made between the 2002 idea and the MTURK service.
### Technical Application: Solving Low-False Positive Web Security Issues via Human Input
- Summary: The initial technical driver for the human-task concept was the need for highly accurate, agentless, remote detection of defaced websites, a problem where traditional algorithms likely generated too many false positives.
- Source: Derived from the context provided about concerns during the development of "e-or."