Tag Archives | AI ethics

The Difference Between AI Ethics in Theory and in Practice

AI and ethics difference between theory and practical application artificial intelligence images

As we move forward in the age of artificial intelligence, the ethics of AI become crucial to product design. What seems ethical when developing AI products – programming machines with the ability to choose right from wrong – often changes when putting those products into practice.
With body cameras worn by police officers, AI technology allows for facial recognition that could assist in suspect identification. After all, memory can become foggy over time, while what a camera sees may be hard evidence. But what happens when facial recognition leads to bias and prejudice? 

While humans must program machines with ethics in mind, machines lack human reasoning–important when deciding what happens when things don’t go exactly as planned. When AI technology fails, as in the case of the autonomous vehicle that struck and killed a pedestrian, an innocent person is the victim.

David Danks, Carnegie Mellon University philosophy and psychology professor, says the people developing the technology must take into account both – ethics and the business goal – and realize “it is not a zero sum gain. It’s not ethical or profitable, where those are mutually exclusive. It’s not ethical or fast, where those are mutually exclusive.”

Many companies will consider ethical implications of AI when designing products, but only occasionally create dedicated ethics groups to focus on questionable uses of the technology by humans when it’s in practice. Of course, technological flaws and failures must also be taken into account.

Basic AI Design Considerations

Many companies will consider ethical implications of AI when designing products, but only occasionally create dedicated ethics groups to focus on questionable uses of the technology by humans when it’s in practice. Of course, technological flaws and failures must also be taken into account.

Controls must be built in to identify biases, show attribution, and enable course correction as needed. To that end, Constellation Research, a technology research and advisory firm based in Silicon Valley, suggests instilling these five design pillars for AI ethics in all projects:

  1. Transparent: Algorithms, attributes, and correlations should be open to inspection for all participants.
  2. Explainable: Humans should be able to understand how AI systems come to their contextual decisions.
  3. Reversible: Organizations must be able to reverse the learnings and adjust as needed.
  4. Trainable: AI systems must have the ability to learn from humans and other systems.
  5. Human-led: All decisions should begin and end with human decision points.

Learn More About Ethics in Design

Mark your calendar and register today for IEEE’s free webinar on Artificial Intelligence and Ethics in Design, taking place at 1:00 p.m. EST, May 9, 2018. You’ll learn how to help your organization apply the theory of ethics to the design and business of AI systems.

The webinar is the perfect companion to Artificial Intelligence and Ethics in Design, a five-course training created to educate and empower professionals to practically implement ethical considerations when developing intelligent and autonomous products and services.


Bhavsar, Vrajesh, ARM. (25 Jan 2018). The development of AI ethics must keep pace with innovation. VentureBeat.

Cook, John. (9 Feb 2018). The ethics of AI: Robots will rise, but will they rule us all? GeekWire.

Fingas, Jon. (26 April 2018). Axon opens ethics board to guide its use of AI in body cameras. Engadget UK.

Wang, R “Ray.” (26 Mar 2018). Designing Five Pillars for Level 1 Artificial Intelligence Ethics. Enterprise Irregulars.

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Preparing Your Business for the Post-AI World (a.k.a. Right Now)

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The world of Artificial Intelligence (AI) isn’t on the horizon; it’s right here, happening right now. AI is the technology behind personal digital assistants like Apple’s Siri and Google’s Alexa, targeted online advertising, more informed medical diagnoses, high-frequency trading, and HR specialists’ resume review processes.

AI has applications in virtually every industry. It has enormous power and potential to disrupt, innovate, enhance and, in many cases, totally transform a business. With the right strategy in place, an investment in AI pays off in big ways, including:

  • Cost reductions
  • Higher productivity
  • Increased revenue and profits
  • Richer customer experiences
  • Working-capital optimization
  • Broader business success

7 Steps to AI Prep

If your business isn’t quite there yet, no need to worry. Simply follow the steps below to help your business jump on the AI train and make the most of the great opportunities this technology presents.

1. Lay the Groundwork: 

  • Familiarize yourself with AI and what it can do for your business. AI technology is constantly evolving, so be sure to keep up with the latest developments and the impact they can have on your industry.
  • Determine and prioritize the most important areas in which AI can benefit your business. Start with the outcomes you want to achieve and work your way back, looking for places where AI can help.
  • Make sure you have a solid IT infrastructure that can handle the change.

2. Unlock Data Silos

Clearing obstacles created by functional silos or disconnected technologies will allow a flow of data within your organization, which is crucial for successful AI implementation.

AI IEEE professional development courses continuing education artificial intelligence3. Label Business Data

AI has limited ability to analyze data and produce insightful information without labels.

4. Feed AI Algorithms with Data and Context

Most AI algorithms are proficient at determining correlations, but they need context. The algorithms don’t understand the information surrounding the data, which may or may not be relevant.

5. Assess Existing Processes

Thoroughly evaluate all departments within your organization and all processes within each. Automating some of the tasks may help ensure that your personnel focuses on tasks that deliver more value.

To determine the areas of great opportunities and eliminate time- and effort-consuming responsibilities, ask your employees:

  • What are the low-value aspects of jobs that could be removed?
  • Which repeatable tasks take a lot of time?

6. Communicate What’s Coming

Change management will do wonders for your AI strategy implementation. It will be particularly important to communicate the end goal, as well as how employees’ jobs will change.

7. Invest in Your Employees’ AI Education:

Jody Kochansky, head of the Aladdin Product Group at financial services firm BlackRock, explains, “Ultimately, the combination of humans plus computers is more powerful than humans alone, and certainly more powerful than computers alone.”

Given the potential of AI to complement human intelligence, it’s vital for top-level executives to be educated about reskilling possibilities. However, according to the 2017 “Is Your Business AI Ready” report from Genpact, 82 percent of companies surveyed plan to implement AI in the next three years, but only 38 percent say they currently provide their employees with reskilling opportunities.

Ready to Make the Investment?

Ensuring opportunities for your employees to become AI-knowledgeable will increase the chances of successful adoption of the new technology and guarantee competitive advantage in the long-term. Train workers who are being moved from jobs that are automated by AI to jobs in which their work is augmented by AI. With the right pieces in place, workforces will not just survive but also thrive alongside automation.

A great place to start your employees’ AI education is with IEEE. Our new AI and Ethics in Design training course will help your organization apply the theory of ethics to the design and business of AI systems. Pre-order Part 1 today and train everyone in your organization for one low price.


Spektor, Nancy. (4 April 2018). How to Prepare Your Business Data for Artificial Intelligence. Smart Data Collective.

Is Your Business AI-Ready? Genpact.

Harrist, Margaret. (28 February 2017). Prepare Your Business For The AI Future. Forbes.

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