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‘Ethical AI’ matters — the problem lies in defining it

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News that Microsoft will invest around $1 billion to examine ethical artificial intelligence signals that the tech sector is thinking deeper about the ethics underlying transformative technologies. But what is ethical AI?

Microsoft is to invest around $1 billion into the OpenAI project, a group that has Elon Musk and Amazon as members. The partners are seeking to establish “shared principles on ethics and trust”. The project is considering two streams: cognitive science, which is linked to psychology and considers the similarities between artificial intelligence and human intelligence; and machine intelligence, which is less concerned with how similar machines are to humans, and instead is focused on how systems behave in an intelligent way.

With the growth of smart technology comes an increased reliance for humanity to place trust in algorithms, that continue to evolve. Increasingly, people are asking whether an ethical framework is needed in response. It would appear so, with some machines now carrying out specific tasks more effectively than humans can. This leads to the questions ‘what is ethical AI?’ and ‘who should develop ethics and regulate them?’

AI’s ethical dilemmas

We’re already seeing examples of what can go wrong when artificial intelligence is granted too much autonomy.Amazon had to pull an artificial intelligence operated recruiting tool after it was found to be biased against female applicants. A different form of bias was associated with a recidivism machine learning-run assessment tool that was biased against black defendants. The U.S. Department of Housing and Urban Development has recently sued Facebook due to its advertising algorithms, which allow advertisers to discriminate based on characteristics such as gender and race. For similar reasons Google opted not to renew its artificial intelligence contract with the U.S. Department of Defense for undisclosed ethical concerns.

These examples outline why, at the early stages, AI produces ethical dilemmas and perhaps why some level of control is required.

Designing AI ethics

Ethics is an important design consideration as artificial intelligence technology progresses. This philosophical inquiry extends from how humanity wants AI to make decisions and with which types of decisions. This is especially important where the is potential danger (as with many autonomous car driving scenarios); and extends to a more dystopian future where AI could replace human decision-making at work and at home. In-between, one notable experiment detailed what might happen if an artificially intelligent chatbot became virulently racist, a study intended to highlights the challenges humanity might face if machines ever become super intelligent.

While there is agreement that AI needs an ethical framework, what should this framework contain? There appears to be little consensus over the definition of ethical and trustworthy AI. A starting point is in the European Union document titled “Ethics Guidelines for Trustworthy AI“. With this brief, the key criteria are for AI to be democratic, to contribute to an equitable society, to support human agency, to foster fundamental rights, and to ensure that human oversight remains in place.

These are important concerns for a liberal democracy. But how do these principles stack up with threats to the autonomy of humans, as with AI that interacts and seeks to influencing behavior, as with the Facebook Cambridge Analytica issue? Even with Google search results, the output, which is controlled by an algorithm, can have a significant influence on the behavior of users.

Furthermore, should AI be used as a weapon? If robots become sophisticated enough (and it can be proven they can ‘reason’), should they be given rights akin to a human? The questions of ethics runs very deep.

OpenAI’s aims

It is grappling with some of these issues that led to the formation of OpenAI. According to Smart2Zero, OpenAI’s primary goal is to ensure that artificial intelligence can be deployed in a way that is both safe and secure, in order that the economic benefits can be widely distributed through society. Notably this does not capture all of the European Union goals, such as how democratic principles will be protected or how human autonomy will be kept central to any AI application.

As a consequence of Microsoft joining of the consortium, OpenAI will seek to develop advanced AI models built upon Microsoft’s Azure cloud computing platform. There are few specific details of how the project will progress.

Commenting on Microsoft’s big investment and commitment to the project, Microsoft chief executive Satya Nadella does not shed much light: “AI is one of the most transformative technologies of our time and has the potential to help solve many of our world’s most pressing challenges…our ambition is to democratize AI.”

Do we need regulation?

It is probable that the OpenAI project will place business first, and it will no doubt seek to reduce areas of bias. This in itself is key to the goals of the partners involved. For wider ethical issues it will be down to governments and academia to develop strong frameworks, and for these to gain public acceptance, and then for an appropriate regulatory structure to be put in place.

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How can the value of the cloud evolve between now and 2030?

According to McKinsey research, large enterprises aim to have about 60% of their environment in the cloud by 2025.

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Cloud technology has become an integral part of the digital transformation of today’s businesses. And that has executives asking themselves important questions — namely, how large is the value at stake in my sector? How quickly will this value be captured? Who will capture it? What can I do to ensure my organization gets its share? 

The answers are multifaceted, and were sought by researchers at McKinsey through a recent analysis. They conducted a thorough review of several key resources, including the McKinsey D2020 IT spending structure benchmarking study, and independent third-party surveys of more than 1,000 organizations that have adopted cloud technologies. Researchers addressed over 700 use cases across 20 different sub industries, ultimately to inform their conclusions, which we’ll cover more below.

Organizations That Maximize Cloud Value Do So In a Combined Approach

The first prominent finding of McKinsey’s review is a prominent trend among organizations that maximize cloud value. According to analysts, those that make the most of the technology do so in a three-pronged system:

Rejuvenate – IT cost optimization, resilience improvement, and core operations digitization

Innovate – innovation-driven growth, accelerated product development, and hyper scalability

Pioneer – early adoption of cloud technology

The Potential Value Waiting To Be Unlocked In Cloud Technology

Another important finding of the review, McKinsey researchers suggest that the potential value in cloud technology is substantial. After analyzing the value at stake for adoption in US Fortune 500 companies, they estimated that up to $1 trillion in annual value is waiting to be unlocked by 2030. Moreover, when applying those same drivers to Forbes Global 2000 companies, the potential value is estimated to be around $3 trillion in EBITDA (Earnings before interest, taxes, depreciation, and amortization) over the next decade.

Asia’s Potential for EBITDA Gains

The report noted that Asia is in line to reap the highest cloud value potential from adoption at about $1.3 trillion by 2030. The continent’s businesses make up the largest regional revenue share of the Forbes Global 2000 companies analyzed, many of which fall within the oil, gas and banking industries. These are sectors which McKinsey researchers have identified as having particularly high potential for value gains from cloud adoption.

The Americas aren’t far behind, coming in second with a potential cloud value of around $1.2 trillion, driven largely by retail and manufacturing sub industries. These specific domestic sectors stand to capture nearly $162 Billion in EBITDA growth by 2030 – more than three times the value potential for those in Asia and the European Union.

The Keys to Unlocking Value

McKinsey interviewed more than 50 CTOs, CIOs, and cloud program leaders from prominent North American enterprises to better understand their work and what success factors they had in common. The research concluded that the most successful cloud adopters leveraged three key levers:

1. Discovering the full value of the cloud.
2. Solving critical technical challenges.
3. Delivering fundamental, organizational change.

These organizations withstood the challenges of cloud adoption and emerged better-positioned to capture value. Their key takeaway was that creating an effective cloud program requires a combination of technical and organizational capabilities, as well as the right mindset. This means that even if an organization has the necessary tools, they may still need to make changes in areas such as strategy, culture, and processes in order to fully benefit from cloud technology.

Read the full report from McKinsey

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WeaveSphere: 5 conference highlights

The WeaveSphere tech conference wove together ideas about AI, FinTech, STEM education, innovation in Canada, and more.

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For three days this November, innovation, collaboration, and a whole lot of big ideas were shared among “Weavers” during the WeaveSphere tech conference in Toronto.

“Today is an opportunity for greater connection between the scientific and tech industry, and academia,” said Marcellus Mindel of IBM Canada, opening the conference. With innovation the event’s core, Mindel added: “let’s define innovation, thinking of it as reframing that implements better outcomes.”

While lots happened over three days, here are five highlights and takeaways from the event:

1. Thought-provoking keynotes had attendees thinking big

Each day of WeaveSphere kicked off with a keynote, where three speakers brought their insightful ideas to attendees.

Gillian Hadfield shared ideas about AI and regulation

On Day 1, Gillian Hadfield, Professor of Law and director of the Schwartz Reisman Institute for Technology and Society at the University of Toronto, explained where we are today when it comes to regulating artificial intelligence (AI) — and where we need to go next. 

While AI makes machines intelligent, Hadfield argued that it cannot, by definition, produce intelligent behaviour if it isn’t functioning appropriately and ethically. Machine learning is not the same as standard programming, since machines write the rules. As a result, machines can start solving problems in ways we don’t want them to, resulting in regulatory challenges. 

How to solve this? Hadfield presented two solutions:

  1. Establish compensation for harm
  2. Design incentives for meeting good and safe behaviour

Dr. William Barry discussed ethics with an AI co-presenter

On Day 2, professor, AI ethicist, and futurist Dr. William Barry talked about a particular problem: what ethical questions might arise when you program a robot? 

For starters, how do you determine what information to include or not? Where is the appropriate line? 

As a professor, Dr. Barry has been working with robots as teaching assistants in his classroom since 2015, and brought a digital version of Maria Bot (one of his AI assistants) to interact with the audience.

As Dr. Barry explained, he is very strategic when choosing the information from which his assistants learn. 

One place Maria won’t get access to? Twitter, says Dr. Barry, highlighting it’s too much of a risk for an “AI benign” to get access to misinformation. This would distort the ethical perspective that Maria is learning, he said. 

While he has programmed her to weed out and to not learn from toxic content — like racism and misogyny — Dr. Barry does work at exposing his AI beings to a wide range of diverse thought and lived experiences. In the end, how ethical an AI being is, is in the hands of the human controlling what they learn, he argued. As a result, they’ll ultimately be biased as a result of the specific data sets we provide for them. 

Marcel Mitran discussed technology for good

WeaveSphere’s Day 3 keynote took a slight turn away from AI. 

IBM Fellow, IBM Master Inventor, and CTO for Cloud Platform for zSystems and LinuxONE, Marcel Mitran took to the main stage for a keynote on responsible computing. At the heart of his talk was the argument that technologists need to take a step back and look at what’s being done to keep the world safe. 

For example, the opportunity for error and bias in the role of facial recognition in public safety, and the fact that our digital footprints — both on a personal level and for enterprise — have grown significantly even in the last year.

As Mitran explained, responsible computing is a systemic, holistic approach addressing current and future computing challenges like sustainability, ethics, and professionalism. It advances the “quadruple bottom line” of people, planet, prosperity, and participation. 

2. Insightful sessions had attendees thinking deep

Photo courtesy WeaveSphere

FinTech, cryptocurrency, AI, digital economies, Canada’s innovation landscape — there was a large cross-section of topics covered across a variety of workshops, paper presentation, and panel discussions. 

Some highlights include:

Chhavi Singh, co-founder of Flyte, asked the question: have you considered using AI to coach your sales staff? Elaborating on the opportunity AI presents to increase sales performance, Singh explained how AI can be used to help understand customer challenges and handle objections and concerns. 

COO of wealth management platform OneVest, Jakob Pizzera, outlined the three phases of FinTech. The first (1.0) was in-house sites for basic online banking. Version 2.0 was the “unbundling” of financial services, and the rise of standalone businesses. The last few years has brought FinTech 3.0, with embedded finance — for example making a purchase through Instagram.

WeaveSphere conference chair and R&D specialist Vio Onut answered the question of why we need to care about cyber security. For starters, the potentially very large costs to your organization, and because the massive skills gap of privacy and security experts has created vulnerabilities. 

Digital strategist Matt Everson explored what can go with emerging technologies like Web3 and the metaverse. Everson said developers should just start building and drawing on video game virtual markets as a model. He used popular online game EVE Online as an example of how virtual economy design can be translated to other markets.

Lijia Hou, Blockchain Systems Engineer with Draft Kings, explained that three key problems still exist when it comes to blockchain technology. First, investors want to understand how — in a volatile market — to mitigate risk. Second, developers from the traditional software side need a mindset shift when it comes to decentralization. And finally, the tools of decentralization are used differently, and this is not always evident for those unfamiliar with Web3.

3. There was a LOT of interest in STEM education

As part of WeaveSphere’s Education Day slate of programming, hundreds of high school and university students had the opportunity to workshop real-life problems from both school and work — all under the guidance of IBM’s Design Thinking experts

Photo courtesy WeaveSphere

This meeting of next-generation tech talent collaboratively explored Enterprise Design Thinking strategies like As-Is Scenario Mapping, Empathy Mapping, Hills (positioning statements), and Hopes and Fears. This approach to problem-solving works by framing the issue at hand in a human-centric way, centering the end-user in all decision-making. 

For Education Day, the problem at hand was helping fourth-year university students find their first job. 

Photo courtesy WeaveSphere

4. There were loads of networking and learning opportunities

One of the best parts of any conference is the opportunity to network and learn from fellow attendees.

In the conference’s Innovation Valley section, event sponsors were on-hand to discuss everything from their latest technologies to job opportunities, plus several graduate students were also there to present their research.

Since WeaveSphere is a “meeting of the minds” between tech professionals and students, many undergrads from schools like York University and Mohawk College came to the conference full of questions, ready to absorb everything. 

5. WeaveSphere celebrated top tech talent

A big part of WeaveSphere was a celebration of some of the best tech minds in Canada. 

During a gala evening at the end of Day 2, the 2022 Developer 30 Under 30 and Tech Titans were awarded to the best of the best among young developers and digital transformation leaders in Canada. 

The winners were:

Developer 30 Under 30 winners

Photo courtesy WeaveSphere
  • Alexander Newman
  • Anakha Chellakudam
  • Anthony Langford
  • Arshdeep Saini
  • Aryaman Rastogi
  • Bohdan Senyshyn
  • Charlie Mackie
  • Charmi Chokshi
  • Colin Lee
  • Daniel Marantz
  • Francisco Hodge 
  • Hassan Djirdeh
  • Jerry Fengwei Zhang
  • Julia Paglia
  • Karandeep Bhardwaj
  • Kathryn Kodama
  • Khushbu Patel
  • Lianne Lardizabal
  • Lucas Giancola
  • Mathew Mozaffari
  • Maz Mandi
  • Oleksandr Kostrikov
  • Rishab Kumar
  • Samantha Lauer
  • Sarah Syed
  • Stan Petley
  • Tanmay Bakshi
  • Tim Romanski
  • Xiaole Zeng
  • Yash Kapadia

Tech Titans winners

Photo courtesy WeaveSphere
  • Andrew Dolinski
  • Ashish Agrawal
  • Chhavi Singh
  • Chris Dolinski
  • Dean Skurka
  • Demetrius Tsafaridis
  • Fay Arjomandi
  • Harish Pandian
  • Harpreet Gill
  • Iman Bashir
  • James Stewart
  • Len Covello
  • Manav Gupta
  • Marcel Mitran
  • Michelle Joliat
  • Dr. Mohamad Sawwaf
  • Omar A. Butt
  • Peter Zwicker
  • Ryan McDonald
  • Dr. William Cherniak

Finally, as WeaveSphere came to a close, the Pitch Stadium opened, hearing from a wide variety of startups. 

They came, they pitched, and in the end, Iman Bashir and Nicole Lytle of Craftly.AI, a copywriting assistant that uses AI to generate original content, took home the $50,000 prize to help grow their business.

Photo courtesy WeaveSphere

WeaveSphere was a uniquely collaborative, innovation-focused conference filled with engaging workshops, presentations, and networking opportunities.


DX Journal is an official media partner for WeaveSphere. Check out our series of articles from the lead-up to WeaveSphere.

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7 Digital Transformation trends on the horizon for 2023

Salesforce’s MuleSoft reports seven trends that are key to balancing operational pressure and improved customer and employee experience.

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Efficiency and growth are at the heart of many a business plans right now, even though an economic downturn is widely predicted to be on the horizon.

In the face of these organizational pressures, Salesforce’s MuleSoft recently released a report detailing their predictions and insights for digital transformation in 2023. In the report, they outlined seven trends that are going to be crucial for organizations that want to overcome these pressures while keeping the gas on customer and employee experiences. 

As MuleSoft Global Field CTO Matt McLarty explained, “as companies gear up for the year ahead, businesses must recognize that effectively utilizing new digital techniques is the only way to ensure growth amidst economic pressures.” 

“Investing in cost efficient, employee- and customer-centric technologies will be critical for companies seeking to remain agile and break away from the competition in 2023.” 

Here are MuleSoft’s seven digital transformation trends-to-watch:

Increase in automation investment

MuleSoft’s research has validated what many in the industry have already predicted regarding the projected growth of automation tools. According to a previous survey, roughly 80% of organizations plan on incorporating hyperautomation into their technology roadmap within the next 24 months. This points to a paradigm shift in the way businesses operate, as they move away from reliance on manual processes to a more digitized and technology-enabled future.

Composability is key

MuleSoft and Salesforce predict that in lieu of the point mentioned above, companies will be inclined to implement strategies like low/no-code platforms and application programming interfaces (APIs) to make their automation efforts more composable.

The rise of low/no-code tools

The report from September found that 73% of leaders agree that acquiring IT talent is the hardest it’s ever been, which makes perfect sense given the global shortage of software developers. In order to free up resources and enable a wider range of employees to participate in digital transformation, low/no-code platforms will continue to grow in popularity.

Investment In total experience (TX) strategies

Amid findings that 86% of IT leaders believe that both employee and customer experience (EX and CX) are as important as a company’s products, MuleSoft’s research anticipates that organizations will increase their focus on delivering great experiences through loyalty and advocacy.

CX and EX initiatives will work in tandem to increase revenue and retain talent, focusing on integration and automation that connect the dots where these two meet.

Data-Driven Decision Making Should Be Technology’s Job

Salesforce research highlights that 83% of organizations consider data-driven decisions to be a top priority in their organization. This data, however, is often siloed. As a result, MuleSoft predicts, 2023 will see the rise of real-time analytics to bread down silos, to “create a data fabric that provides automated, intelligent, and real-time insights and reduces untimely decisions.”

Cybersecurity Is Set to Scale

Expect to see more organizations invest in a cybersecurity mesh approach in order to secure data as it moves between multiple cloud applications. This is in response to data from Gartner that claims doing so could reduce the financial impact of security incidents by 90%.

Sustainability Will Be a Priority

Organizations are likely to increase their adoption of data-driven insights and integration across supply chains as they seek to become more sustainable. 


Download the full Mulesoft report

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