Since OpenAI released ChatGPT in November 2022, we have seen increased excitement about generative artificial intelligence (AI), coupled with concerns about its safety. Given this inflection point, we must pay renewed attention to its impact on the future of knowledge work carried out by professionals. This is because compared to earlier types of AI, generative AI gets closer to the core activities of professionals, namely giving advice to and treating clients. And yet, how and how fast professionals' work will change is not well understood. Instead of leaving the issue to be part of "unintended consequences,"3 this column argues that we can influence how generative AI will become embedded in the work we do as professionals. Professionals in a variety of fields--including medicine, audit, accounting, law, and data science--are essentially in the business of diagnosis and treatment, connecting the two via inference.

"…In many organizations, the human resource department is responsible for many strategic tasks from managing the hiring to [the] termination of employee[s], for example monitoring of employees' at all the levels, handling payroll, managing employee[s'] benefits and so on. To make this work easier[,] organizations across the world are investing in HR automation [to] [carry] out the best human capital decision[s]…" I know what you're thinking: "…my company's board of directors is too visually impaired to consider what kind of impact these new-flanged capabilities will have on the company to actually consider them-- let alone implement them…" but you would be wrong to think this way; because the change is not only already happening, but it is accelerating. While it is true that some companies have not fully considered implementing a complete, top-to-bottom HR automation strategy -- largely because such a thing is still too abstract a problem and a not-so-clear-opportunity right now -- news like Amazon's drive to automate hiring and onboarding for its hourly warehouse workers will not stay secret for long. Do not kid yourselves, while corporate boards are not known for being bastions of innovation and forward-thinking, they know it's possible -- even if they are unable to see its affect on the corporation's current business -- at least, not yet, anyway.

If you are a software engineer or a data scientist, your job did not exist a century ago. A century from now, your job will most likely look quite different. One driving force behind such work transformation is artificial intelligence (AI). Dwelling on the nearer term, the next decade or two, projections on the proportion of today's jobs that are susceptible to automation vary enormously--from 9% (in OEDC countries)2 and 47% (of 702 occupations)7 to 96% (740 out of 769 occupations).6,8,9 Why is there such wide variation?

A new research paper by Google researchers Hui Fang and Meng Zhang has outlined their attempt to teach Google's AI how to take aesthetically pleasing photos. Creatism: A deep-learning photographer capable of creating professional work are the researchers attempt to apply machine learning to the creative process. The first step was to define different aesthetic aspects of photography like composition, saturation and detail. They then analyzed 15,000 high-ranking photo thumbnails from 500px.com so the neural network could begin to understand which cropping and lighting effects were the most popular. The next step was to unleash the machine on Google Street View and let it take snapshots of scenic locations and crop and light the results accordingly.

For the first time since 1992, the ACM Code of Ethics and Professional Conduct (the Code) is being updated. The Code Update Task Force in conjunction with the Committee on Professional Ethics is seeking advice from ACM members on the update. We indicated many of the motivations for changing the Code when we shared Draft 1 of Code 2018 with the ACM membership in the December 2016 issue of CACMb and with others through email and the COPE website (ethics.acm.org). Since December, we have been collecting feedback and are vetting proposed changes. We have seen a broad range of concerns about responsible computing including bullying in social media, cyber security, and autonomous machines making ethically significant decisions. The Task Force appreciates the many serious and thoughtful comments it has received. In response, the Task Force has proposed changes that are reflected in Draft 2 of the Code. There are a number of substantial changes that require some explanation. In this article, we discuss these, and we explain why we did not include other requested changes in Draft 2. We look forward to receiving your comments on these suggested changes and your requests for additional changes as we work on Draft 3 of the Code. We have provided opportunities for your comments and an open discussion of Draft 2 at the ACM Code 2018 Discussion website [http://code2018.acm.org/discuss]. Comments can also be contributed at the COPE website https://ethics.acm.org, and by direct emails to chair@ethics.acm.org. ACM members are part of the computing profession and the ACM's Code of Ethics and Professional Conduct should reflect the conscience of the computing profession.

Robots have transformed the lives of tradesmen and laborers, but lawyers, architects, and doctors tend to believe that their careers are safe from the advances of artificial intelligence. This belief is entirely wrong, according to the upcoming book, Future of the Professions: How Technology will Transform the Work of Human Experts. The authors, Richard Susskind, UK government advisor and visiting professor at Oxford Internet Institute, and his son Daniel Susskind, lecturer at Oxford University, have conducted a hundred interviews and drawn on economic and sociological theory to reach their challenging conclusion: AI will dramatically transform the middle-class working landscape. In the near-term, the Susskinds argue, artificial intelligence will simply accelerate the efficiency of professions. But then robots will start to take over more work, and humans will find the roles of "doctor" or "lawyer" replaced with such less glamorous-sounding titles as "empathizer," "knowledge engineer," or "system provider."