Unlocking the Potential of Engineered Intelligence: AI’s Dynamic New Ally

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We stand on the edge of a fourth AI winter, as confidence wanes regarding AI’s ability to deliver substantial value that justifies its costs. While insightful analyses from firms like Goldman Sachs and various research institutions continue to surface, there remains a window of opportunity to stave off this impending AI winter. The solution has been in plain sight for years.

Identifying the Gap in AI Development

In most scientific fields, groundbreaking discoveries occur in laboratories and are subsequently transferred to engineers for real-world implementation. For example:

• When chemical researchers discover a novel adhesive bonding technique, chemical engineers apply it to create products.
• Mechanical breakthroughs made by physicists are passed to mechanical engineers to devise applicable solutions.

However, when it comes to AI breakthroughs, there is no dedicated discipline for applied artificial intelligence. This gap leads organizations to hire data scientists, who are often PhD holders intent on making scientific advances in AI, but instead find themselves trying to develop practical solutions. The outcome? A staggering 87% of AI projects fail.

Introducing Engineered Intelligence

“Engineered intelligence” (verb: “intelligence engineering”) is an emerging field focused on the practical application of AI research through engineering principles. It aims to harness scientific breakthroughs and raw materials to design and develop safe and effective solutions. This approach empowers domain experts, scientists, and engineers to create intelligent solutions without the necessity of becoming data scientists.

Leading industrial entities are pursuing new avenues by:

• Revitalizing research-to-engineering pipelines,
• Forming partnerships with academic institutions and tech vendors,
• Creating an ecosystem where AI research can effectively transition to intelligence engineers, mimicking the way chemical research is integrated with chemical engineering.

This shift leads to:

• Groundbreaking applications that add tangible value,
• Solutions that make it to production, and
• Innovations that might not have been discovered by data scientists or tech vendors using data alone.

5 Steps to Implement Intelligence Engineering in Your Organization

At the core of intelligence engineering is expertise, represented by skills — the building blocks of knowledge cultivated through hands-on experience. Although training can expedite skill acquisition, true expertise can only emerge from practical engagement. If your organization already possesses experts, follow these five practical steps to integrate intelligence engineering and differentiate it from traditional AI approaches:

The conventional method for introducing AI (accounting for the 87% failure rate) is:

1. Create a list of problems.

Alternatively, it often includes:

1. Examining your data.
2. Identifying potential use cases.
3. Analyzing use cases for return on investment (ROI), feasibility, cost, and timeline.
4. Selecting a subset of use cases and investing in execution.

In contrast, the intelligence engineering process for implementing engineered intelligence is as follows:

1. Create a heatmap to identify the expertise present in your existing processes.
2. Evaluate which areas of expertise hold the most value for your organization and assess the abundance or scarcity of that expertise.
3. Select the top five most valuable and scarce areas of expertise within your organization.
4. Analyze these for ROI, feasibility, cost, and timeline to engineer intelligent solutions.
5. Choose a subset of valuable use cases and allocate resources for execution.

Forging a New Path to Value with AI

Once the principles of intelligence engineering are established and intuitive applications are implemented, this new capability can transcend current expertise to unveil new opportunities for crafting safe, practical solutions throughout the organization and its ecosystem.

As organizations, industries, and academic institutions build frameworks for engineered intelligence, a myriad of benefits will emerge—unlocking economic and societal potential that would otherwise go unrealized, generating new job categories, and sparking a fresh wave of value creation across all sectors

Source:  https://venturebeat.com/ai/introducing-ais-long-lost-twin-engineered-intelligence/