In this blog post series, Amalgam Insights is providing a practical model for businesses to plan the ethical governance of their AI projects. To read the introduction, click here. To read about Stage 1: Executive Design, click here To read about Stage 2: Technical Development, click here. This blog focuses on Operational Deployment, the third of…
In this blog post series, Amalgam Insights is providing a practical model for businesses to plan the ethical governance of their AI projects. To read the introduction, click here. To read about Stage 1: Executive Design, click here This blog focuses on Technical Development, the second of the Three Keys to Ethical AI described in the…
In this blog post series, Amalgam Insights is providing a practical model for businesses to plan the ethical governance of their AI projects. To read the introduction, click here. This blog focuses on Executive Design, the first of the Three Keys to Ethical AI introduced in the last blog. Stage I: Executive Design As a…
As we head into 2020, the concept of “AI (Artificial Intelligence) for Good” is becoming an increasingly common phrase. Individuals and organizations with AI skillsets (including data management, data integration, statistical analysis, machine learning, algorithmic model development, and application deployment skills) have effort into pursuing ethical AI efforts.
Amalgam Insights believes that these efforts have largely been piecemeal and inadequate to meet common-sense definitions for companies to effectively state that they are pursuing, documenting, and practicing true ethical AI because of the breadth and potential repercussions of AI on business outcomes. This is not due to a lack of interest, but based on a couple of key considerations. First, AI is a relatively new capability in the enterprise IT portfolio that often lacks formal practices and guidelines and has been managed as a “skunkworks” or experimental project. Second, businesses have not seen AI as a business practice, but as a purely technical practice and made a number of assumptions in skipping to the technical development that would typically not have been made for more mature technical capabilities and projects.
In the past, Amalgam Insights has provided frameworks to help organizations take the next step to AI through our BI to AI progression.
To pursue a more ethical model of AI, Amalgam Insights believes that AI efforts need to be analyzed through three key lenses:
- Executive Design
- Technical Development
- Operational Deployment
Figure 2: Amalgam’s Three Key Areas for Ethical AI
In each of these areas, businesses must ask the right questions and adequately prepare for the deployment of ethical AI. In this framework, AI is not just a set of machine learning algorithms to be utilized, but an enabler to effectively augment problem-solving for appropriate challenges.
Over the next week, Amalgam Insights will explore 12 areas of bias across these three categories with the goal of developing a straightforward framework that companies can use to guide their AI initiatives and take a structured approach to enforcing a consistent set of ethical guidelines to support governance across the executive, technical, and operational aspects of initiating, developing, and deploying AI.
In our next blog, we will explore Executive Design with a focus on the five key questions that an executive must consider as they start considering the use of AI within their enterprise.
On July 22, Microsoft announced a $1 billion investment in OpenAI, a lab focused on “artificial general intelligence,” or the goal of creating artificial intelligence with human-like observation and learning capabilities. With this announcement, Microsoft becomes the “exclusive” cloud computing provider for OpenAI and will have access to productizing OpenAI capabilities as they come to market.
Key Takeaways: Microsoft makes a long-term investment in “general intelligence” to start on the next generation of AIs that will be coming to market in five-to-ten years and will be able to recoup some costs back as OpenAI’s cloud provider and monetizer of OpenAI technologies.
At Amalgam Insights, we have been focused on the key 2018 trends that will change our ability to manage technology at scale. In Part 1 of this series, Tom Petrocelli provided his key Developer Operations and enterprise collaboration predictions for 2018 in mid-December. In part two, , Todd Maddox provided 5 key predictions that will shape enterprise learning in 2018. In the third and final set of predictions, I’m taking on key themes of cloud, mobility, telecom, and data management that will challenge IT in terms of management at scale.
- Cloud IaaS and SaaS Spend under formal management will double in 2018, but the total spend under formalized management still be under 25% of total business spend.
- The number of cellular-connected IoT devices will double to over one billion between now and 2020.
- Technology Lifecycle Management will start to emerge as a complex spend management strategy for medium and large enterprises.
- Ethical AI will emerge as a key practice for AI Governance.